text:
@inproceedings{10.1145/3020165.3020190,
author = {Fuhr, Norbert},
title = {Modeling Interactive Information Retrieval as a Stochastic Process},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020190},
doi = {10.1145/3020165.3020190},
abstract = {Stochastic models have a long history in IR, starting from probabilistic models for (non-interactive) IR, and later for evaluation measures like e.g. average precision or discounted cumulated gain. The probabilistic ranking principle defines the order in which a user should inspect the documents retrieved by the system, for maximizing the retrieval quality experienced by the user. In a similar way, for interactive IR, the interactive probabilistic ranking principle (IPRP) defines a framework for the optimum ordering of suggestions / possible actions to be considered by the user.For modeling sequences of interactions, different variants of Markov models have been proposed by a number of researchers. Here a user moves stochastically between different model states, which are not directly observable; instead, some signal is emitted along with each transition. In the simple Markov model, there is a unique mapping from signal sequences to state sequences, while hidden Markov models drop this assumption. In partially observable Markov models, some transitions may not be observable at all. Orthogonal to this distinction, in Markov decision processes, it is additionally assumed that the user achieves a certain gain with each transition.Although the theoretic foundations of these models are well-known, their application to interactive retrieval raises a number of research questions. In the ideal case, we would like to model search progress at a level that is comparable to cognitive models. Thus, as a basic requirement, the states should have some semantic meaning and correspond to different cognitive tasks / states of the user. Moreover, search progress should be somehow reflected by the sequence of states the user passes through. As basic "signals" we have the user's actions which are typically recorded in the system log, and thus easily available for experimentation. Furthermore, other observation data can be collected, such as key logging, mouse movements, eye tracking or EEG data (the latter two types only in lab experiments).There are three major applications of these models. First, and most important, as a realization of the IPRP, they can be used for user guidance. Second, the analysis of these models serves for a detailed, user-oriented analysis of a interactive IR system, pointing out e.g. where users spend most of their time, or where the transition probabilities of specific actions is below the expectation. Third, the models can be used for more realistic stochastic simulations of interactive IR.In this talk, after illustrating the basic concepts, we present some recent research results illustrating the general feasibility of research along these lines.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {1},
numpages = {1},
keywords = {markov models, user guidance, search log analysis},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3038293,
author = {Blandford, Ann E.},
title = {Engaging In Information Interaction},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3038293},
doi = {10.1145/3020165.3038293},
abstract = {People interact with information in a myriad of ways [1]. As well as actively seeking information, people also encounter it, and there have been various efforts to design systems that support encountering and keeping track of encountered information [2,3]. But what people engage with depends: on how it fits with their ongoing activities as well as whether they recognize its potential value [4]. Sometimes, people are open to engaging with information, and may experience information encountering as serendipitous; at other times, a similar encounter might feel like overload or distraction [5]. The design of systems that support effective engagement will ideally take account of people's practices and contexts as well as their interests. Perhaps paradoxically, serendipitous encounters rarely happen by chance: people invest in various ways in increasing the likelihood of valuable information encounters that enable them to keep up-to-date and make creative leaps [6,7]; again, good design can facilitate productive interactions with information [8]. In this talk, I will discuss various qualitative studies of how people fit information encountering into their lives, how they experience serendipity, and some of the ways they invest up-front effort in future information interactions; I will also highlight opportunities to design to support people in making best use of information they find.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {3},
numpages = {1},
keywords = {serendipity, information interaction, situated use},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3038294,
author = {Wium Lie, H\"{a}kon},
title = {CSS and User-Adapted Web Presentations},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3038294},
doi = {10.1145/3020165.3038294},
abstract = {H\r{a}kon Wium Lie proposed Cascading Style Sheets (CSS) while working with Tim Berners-Lee at CERN in 1994. CSS has become a cornerstone web technology which enables beautiful web pages across a range of devices. The CSS specification was developed while H\r{a}kon worked for W3C, and as CTO of Opera Software he shepherded CSS implementations. He is now the chairman of YesLogic, which makes the Prince CSS-to-PDF formatter. He holds a MS from MIT's Media Lab, and a PhD from the University of Oslo.In his keynote, H\r{a}kon will discuss how CSS was designed to allow web content to be presented in different contexts, serving different user needs.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {5},
numpages = {1},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020168,
author = {Hienert, Daniel},
title = {User Interests in German Social Science Literature Search: A Large Scale Log Analysis},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020168},
doi = {10.1145/3020165.3020168},
abstract = {The social sciences are a broad research field with a lot of sub- and related disciplines. Accordingly, user interests in a digital library for the social sciences are manifold. In this study we analyzed nine years log data of a social science digital library to get an overview of the fields, categories, topics and detailed information needs users are interested in. Based on the log data we have built interactive visualizations which give an overview and concurrently let us look at the detailed interests of users. The underlying log data and the created visualizations are then used to analyze user interests at different hierarchical levels and on a temporal view. The results show that there are topical interests of the users in specific fields and topics of the social sciences but at the same time there exists a diversity of different information needs. Based on these findings we analyze in detail the gap between the indexing language of the system used to annotate documents and the language users apply to articulate their information needs.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {7–16},
numpages = {10},
keywords = {social sciences, digital library, user interests, log analysis},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020170,
author = {Papoutsaki, Alexandra and Laskey, James and Huang, Jeff},
title = {SearchGazer: Webcam Eye Tracking for Remote Studies of Web Search},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020170},
doi = {10.1145/3020165.3020170},
abstract = {We introduce SearchGazer, a web-based eye tracker for remote web search studies using common webcams already present in laptops and some desktop computers. SearchGazer is a pure JavaScript library that infers the gaze behavior of searchers in real time. The eye tracking model self-calibrates by watching searchers interact with the search pages and trains a mapping of eye features to gaze locations and search page elements on the screen. Contrary to typical eye tracking studies in information retrieval, this approach does not require the purchase of any additional specialized equipment, and can be done remotely in a user's natural environment, leading to cheaper and easier visual attention studies.While SearchGazer is not intended to be as accurate as specialized eye trackers, it is able to replicate many of the research findings of three seminal information retrieval papers: two that used eye tracking devices, and one that used the mouse cursor as a restricted focus viewer. Charts and heatmaps from those original papers are plotted side-by-side with SearchGazer results. While the main results are similar, there are some notable differences, which we hypothesize derive from improvements in the latest ranking technologies used by current versions of search engines and diligence by remote users. As part of this paper, we also release SearchGazer as a library that can be integrated into any search page.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {17–26},
numpages = {10},
keywords = {user interactions, web search behavior, gaze prediction, online eye tracking, remote user studies},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020167,
author = {O'Brien, Heather L. and McCay-Peet, Lori},
title = {Asking "Good" Questions: Questionnaire Design and Analysis in Interactive Information Retrieval Research},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020167},
doi = {10.1145/3020165.3020167},
abstract = {Asking questions is a central element of Interactive Information Retrieval (IIR) studies, yet the challenges associated with asking "good" questions is are rarely discussed. This perspectives paper examines the development, evaluation, and application of questionnaires in IIR research. The authors draw upon prior literature and their own research to explore how to best construct and extract meaning from questionnaires. Since building IIR knowledge and theories requires the employment of valid, reliable, dimensional, and sensitive self-report measures, this paper's contribution is an overview of best practices for developing, administering, and analyzing questionaires.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {27–36},
numpages = {10},
keywords = {self-report measures, validity, interactive information retrieval, measurement, psychometric scales, evaluation, questionnaires, reliability},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020187,
author = {Buchanan, George R. and McKay, Dana},
title = {Something is Lost, Something is Found: Book Use at the Library Shelves},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020187},
doi = {10.1145/3020165.3020187},
abstract = {This paper investigates the life of books on physical library shelves. Most existing data on the use of library books uses logs to quantify loans, or user interviews to obtain insights into their use. We deploy a new specialised technique, photographing library shelves systematically over a week-long period, and noting the changes to the positioning of individual books, and each shelf as a whole. Through this indirect observation, we demonstrate the use of shelved books within, rather than on leaving, the library. We reveal the first insight into within-library book use, and demonstrate that in-library use appears to be more common and over a longer period than previous research suggests.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {37–46},
numpages = {10},
keywords = {user study, information behaviour, information interaction, libraries},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020179,
author = {McKay, Dana and Chang, Shanton and Smith, Wally},
title = {Manoeuvres in the Dark: Design Implications of the Physical Mechanics of Library Shelf Browsing},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020179},
doi = {10.1145/3020165.3020179},
abstract = {Library shelf browsing is a much-loved but little-understood form of information seeking. Attempts have been made to replicate or replace it online, however they have not typically been based on a principled understanding of the goals and behaviours of readers. This paper addresses the behaviour of readers, presenting an empirical examination of the mechanics of library shelf browsing. We note some previously undescribed behaviours, such as placemarking, and some hitherto unknown details such as the large number of books browsers consider. We situate our findings in the literature, and use them to drive design recommendations.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {47–56},
numpages = {10},
keywords = {observation, interface design, browsing, libraries, books},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020174,
author = {Klouche, Khalil and Ruotsalo, Tuukka and Micallef, Luana and Andolina, Salvatore and Jacucci, Giulio},
title = {Visual Re-Ranking for Multi-Aspect Information Retrieval},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020174},
doi = {10.1145/3020165.3020174},
abstract = {We present visual re-ranking, an interactive visualization technique for multi-aspect information retrieval. In multi-aspect search, the information need of the user consists of more than one aspect or query simultaneously. While visualization and interactive search user interface techniques for improving user interpretation of search results have been proposed, the current research lacks understanding on how useful these are for the user: whether they lead to quantifiable benefits in perceiving the result space and allow faster, and more precise retrieval. Our technique visualizes relevance and document density on a two-dimensional map with respect to the query phrases. Pointing to a location on the map specifies a weight distribution of the relevance to each of the query phrases, according to which search results are re-ranked. User experiments compared our technique to a uni-dimensional search interface with typed query and ranked result list, in perception and retrieval tasks. Visual re-ranking yielded improved accuracy in perception, higher precision in retrieval and overall faster task execution. Our findings demonstrate the utility of visual re-ranking, and can help designing search user interfaces that support multi-aspect search.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {57–66},
numpages = {10},
keywords = {multi-aspect search, information visualization, information retrieval, multi-dimensional ranking},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020188,
author = {He, Jiyin and Yilmaz, Emine},
title = {User Behaviour and Task Characteristics: A Field Study of Daily Information Behaviour},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020188},
doi = {10.1145/3020165.3020188},
abstract = {Previous studies investigating task based search often take the form of lab studies or large scale log analysis. In lab studies, users typically perform a designed task under a controlled environment, which may not reflect their natural behaviour. While log analysis allows the observation of users' natural search behaviour, often strong assumptions need to be made in order to associate the unobserved underlying user tasks with log signals.We describe a field study during which we log participants' daily search and browsing activities for 5 days, and users are asked to self-annotate their search logs with the tasks they conducted as well as to describe the task characteristics according to a conceptual task classification scheme. This provides us with a more realistic and comprehensive view on how user tasks are associated with logged interactions than seen in previous log- or lab-based studies; and allows us to explore the complex interactions between task characteristics and their presence in naturalistic tasks which has not been studied previously.We find a higher number of queries, longer timespan, as well as more task switches than reported in previous log based studies; and 41% of our tasks are zero-query tasks implying that large amounts of user task activities remain unobserved when only focused on query logs. Further, tasks sharing similar descriptions can vary greatly in their characteristics, suggesting that when supporting users with their tasks, it is important to know not only the task they are engaged with but also the context of the user in the task.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {67–76},
numpages = {10},
keywords = {field study, search log analysis, task-based search},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020178,
author = {Hoeber, Orland and Sarkar, Anoop and Vacariu, Andrei and Whitney, Max and Gaikwad, Manali and Kaur, Gursimran},
title = {Evaluating the Value of Lensing Wikipedia During the Information Seeking Process},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020178},
doi = {10.1145/3020165.3020178},
abstract = {While Wikipedia is an excellent source of information about entities, discovering relationships among them is not well-supported by its search features. Lensing Wikipedia was designed as an alternate search and summarization interface, providing a set of filtering, visualization, and exploration tools that enable searching among the connections between people, organizations, and locations. In this paper, we present the results of a user study on how these features are used in each of Vakkari's stages of information seeking (pre-focus, focus formulation, and post-focus), and the participants perceptions of the utility of these features to their overall information-seeking goals. Participants primarily used input and control features during the pre-focus stage, informational and personalization features during the focus formulation stage, and personalization features during the post-focus stage. Findings from this study contribute to understanding how people use advanced search, summarization, and visualization tools to aid their information seeking tasks.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {77–86},
numpages = {10},
keywords = {user study, information seeking, wikipedia search},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020180,
author = {Kotzyba, Michael and Gossen, Tatiana and Schwerdt, Johannes and N\"{u}rnberger, Andreas},
title = {Exploration or Fact-Finding: Inferring User's Search Activity Just in Time},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020180},
doi = {10.1145/3020165.3020180},
abstract = {Being able to differentiate between search activities a user is currently engaged in is crucial for adaptive information retrieval systems in order to provide appropriate support to the user in time. In this paper, we conduct an investigation into modeling two kinds of search activities: exploratory activities and fact-finding activities during web search. Specifically, we consider the case where a user is conducting consecutive fact-finding searches on multiple topics. This information behavior is also known as multitasking search. The goal of our research is to build models of users' web information-seeking behavior in order to differentiate between search activities caused by exploratory search tasks and consecutive fact-finding search tasks while users are still searching. In order to build search process models, we have designed and conducted a user study where the participants interact with a common web search engine. Based on the gathered log data, we built search models based on (Hidden) Markov Models and analyze the results. Our results yield to classification rates between 73.6% and 92.1% using different Markov Models and different data configurations. Furthermore, even with interaction sequences of a limited length, the models reach a classification rate of 85.6% within the first four interactions and about 89% with 30 and more interactions. Using a reduced data set the models still reach an accuracy of 87.7%. That is, within a single session the trained models can be used to detect the search activity to provide appropriate user support.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {87–96},
numpages = {10},
keywords = {recognition, exploratory search, fact-finding search, multitasking search, user study, modeling},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020173,
author = {Kim, Jaewon and Thomas, Paul and Sankaranarayana, Ramesh and Gedeon, Tom and Yoon, Hwan-Jin},
title = {What Snippet Size is Needed in Mobile Web Search?},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020173},
doi = {10.1145/3020165.3020173},
abstract = {A snippet (content summary for a web page) is one of the main elements in a search result page. Search engines have been improved to reduce users' effort in web search, e.g., providing flexible snippet sizes by considering the purpose of the search and suggesting predicted answers. In most cases, search engines for mobile devices present two or three lines of snippet for each result link. Some studies suggest that long snippets provide a better search experience on desktop screens, but this may not be true for mobile devices because of the smaller screen.We conducted a user study to investigate what size of snippet is appropriate for mobile devices. Our findings suggest that users with long snippets on mobile devices exhibit longer search times with no better search accuracy for informational tasks. This is caused by the longer reading time, frequent scrolling with bigger viewport movements, and greater time consumption for searching and reading one result. The overall findings suggest that, unlike desktop users, mobile users are best served by snippets of two to three lines.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {97–106},
numpages = {10},
keywords = {snippet length, search engine result page, mobile web search},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020182,
author = {Singh, Jaspreet and Zerr, Sergej and Siersdorfer, Stefan},
title = {Structure-Aware Visualization of Text Corpora},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020182},
doi = {10.1145/3020165.3020182},
abstract = {Trying to comprehend the structure and content of large text corpora can be a daunting and often time consuming task. In this paper, we introduce a novel tool that exploits the structural properties for extracting and visualizing the underlying topics in a given dataset. To this end, we make use of a combination of latent topic analysis, discriminative feature selection applied on top of the category structure of corpora, and various ranking methods in order to extract the most representative topics for a given corpus. The visual moniker to depict the outcome of these methods can be chosen based on the context. Such visual representations can be useful for depicting trends, identifying ``hot'' topics, and discovering interesting patterns in the underlying data. As applications, we create example representations for a variety of corpora obtained from conference proceedings, movie summaries, and newsgroup postings. Our user experiments demonstrate the viability of our approach, with a flower-like visualization inspired by the ``wheel of emotion'', for generating high quality representative topics and for unearthing hidden structures and connections in large document corpora.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {107–116},
numpages = {10},
keywords = {visualizing topics, latent topics, text corpora, lda, evenness index, visualizing structured text, mutual information, flower},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020183,
author = {Radlinski, Filip and Craswell, Nick},
title = {A Theoretical Framework for Conversational Search},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020183},
doi = {10.1145/3020165.3020183},
abstract = {This paper studies conversational approaches to information retrieval, presenting a theory and model of information interaction in a chat setting. In particular, we consider the question of what properties would be desirable for a conversational information retrieval system so that the system can allow users to answer a variety of information needs in a natural and efficient manner. We study past work on human conversations, and propose a small set of properties that taken together could measure the extent to which a system is conversational. Following this, we present a theoretical model of a conversational system that implements the properties. We describe how this system could be implemented, making the action space of an conversational search agent explicit. Our analysis of this model shows that while theoretical, the model could be practically implemented to satisfy the desirable properties presented. In doing so, we show that the properties are also feasible.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {117–126},
numpages = {10},
keywords = {chatbot, conversational search, personal agent},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020184,
author = {Luo, Cheng and Li, Xue and Liu, Yiqun and Sakai, Tetsuya and Zhang, Fan and Zhang, Min and Ma, Shaoping},
title = {Investigating Users' Time Perception during Web Search},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020184},
doi = {10.1145/3020165.3020184},
abstract = {Due to the tremendous economic value of search result pages, search engine companies have invested a lot to improve their quality. Recently, much effort has been made to directly model key aspects of users' interactions with search system, for example, Benefit and Cost. Time has been widely adopted in both of the two aspects since benefit and cost must be expressed in meaningful units in practical application. Psychological studies have demonstrated that the subjectively perceived time might be different from the objective time measured by timing device and the time perception process of human beings is affected by some psychological factors, such as motivation and interest, which are closely related to the search process. Considering that time is usually used to describe the subject experience of search users, it is necessary to investigate the difference between perceived time and objective time in search process. In psychology, there is a temporal illusion effect named Vierordt's law, i.e. shorter intervals tend to be overestimated while longer intervals tend to be underestimated. In this work, we carefully designed a lab-study to examine the impact of duration length on user's time perception in the context of search. Experimental results show that Vierordt's law is consistently observed in Web search environment. This work could help us to correct the estimation of users' perceived time and provide insights about the mechanism of satisfaction.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {127–136},
numpages = {10},
keywords = {interactive information retrieval, search evaluation, time perception},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020176,
author = {Jiang, Jiepu and He, Daqing and Kelly, Diane and Allan, James},
title = {Understanding Ephemeral State of Relevance},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020176},
doi = {10.1145/3020165.3020176},
abstract = {Despite its dynamic nature, relevance is often measured in a context-independent manner in information retrieval practice. We look into this discrepancy. We propose a contextual relevance/usefulness measurement called ephemeral state of relevance (ESR), which is defined as the amount of useful information a user acquired from a clicked result as assessed just after examining the result during an interactive search session. We collect ESR and context-independent usefulness judgments through a laboratory user study and compare the two. We examine factors related to both judgments and examine their differences.Our study demonstrates a few advantages of ESR: it captures users' real-time state of mind and perceptions; it measures how much useful information the user is able to acquire from a result rather than how much there is in the result; it better reflects users' needs and criteria of useful results during a session, highlighting novelty as a salient factor. However, we also find that users may not be able to correctly assess the credibility of information during a session, which may reduce the reliability of the collected ESR judgments.We evaluate ESR, context-independent usefulness judgments, and TREC-style topical relevance judgments by correlating with user experience in a session. The results demonstrate that switching the judgment criterion from topical relevance to usefulness is fruitful, but moving from context-independent judgments to contextual ones has only limited advantages with respect to its cost and complexity. Our study enriches current understanding on the dynamics of relevance in a search session and identifies both opportunities and challenges for collecting contextual relevance judgments.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {137–146},
numpages = {10},
keywords = {user experience, usefulness, relevance judgment, web search},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020169,
author = {Wilson, Max L.},
title = {The Tetris Model of Resolving Information Needs within the Information Seeking Process},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020169},
doi = {10.1145/3020165.3020169},
abstract = {Theoretical abstractions, of many different aspects of search, have played a crucial role in driving research into human information seeking and retrieval forward. From models of the Information Seeking Process, to how we perceive search systems, these models help us to 1) conceptually formalise and separate aspects of the model's focus, 2) communicate more clearly about these aspects, 3) create hypotheses for subsequent research, and 4) produce implications for future systems. Implicit in these four aspects is that models and theories should have a focus and a purpose. After clarifying the relationships between models, theories, and meta-theories, this perspectives paper introduces the Tetris Model of Resolving Information Needs within the Information Seeking Process, the purpose of which is to better represent the behaviours around the Human Computer Interaction with Information Retrieval, which are often confounded within stage-based models of the Information Seeking Process. In particular, the possible sequence of actions performed by a searcher are typically linearly aligned from left-to-right, and thus imply a temporal progression. The differing focus of the Tetris model is to better capture the temporal experience of searching, by removing the implied progression of left-to-right. The aim of this perspectives paper, therefore, is to introduce this new Tetris Model, such that it can be used to formalise people's interactive experiences in a new way, so that we can more clearly communicate about them, create hypotheses from the model, and consider novel design implications based upon it.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {147–154},
numpages = {8},
keywords = {theory, model, information seeking process, information need},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020177,
author = {Badache, Ismail and Boughanem, Mohand},
title = {Fresh and Diverse Social Signals: Any Impacts on Search?},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020177},
doi = {10.1145/3020165.3020177},
abstract = {In this paper, we extensively study the impact of social signals (users' actions) obtained from several social networks on search ranking task. Social signals associated with web resources (documents) can be considered as an additional information that can play a vital role to estimate a priori importance of these resources. Particularly, we are interested in the freshness of signals and their diversity. We hypothesize that the moment (the date) when the user actions occur and the diversity of actions may impact the search performance. We propose to model these heterogeneous social features as document prior. We evaluate the effectiveness of our approach by carrying out extensive experiments on two different INEX datasets, namely SBS and IMDb, enriched with several social signals collected from social networks. Our experimental results consistently demonstrate the interest of integrating fresh and diverse signals in the retrieval process.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {155–164},
numpages = {10},
keywords = {signals diversity, social networks, social signals, freshness},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020181,
author = {Le, Long T. and Shah, Chirag and Choi, Erik},
title = {Bad Users or Bad Content? Breaking the Vicious Cycle by Finding Struggling Students in Community Question-Answering},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020181},
doi = {10.1145/3020165.3020181},
abstract = {Community Question Answering (CQA) services have become popular methods to seek and share information. In CQA, users with an information need, or askers, post a question that community members can answer. This question-answering process allows both askers and answerers to learn through the exchange of information. CQA services have also been widely used in the education domain, as some of such services are designed specifically for students' information seeking. However, due to insufficient knowledge, lack of experience, and other reasons, students often struggle in producing quality or even appropriate content. This low quality production causes their content to be flagged or deleted, further discouraging them from participating in the CQA process and instigating a vicious cycle of bad users and bad content. In an effort to break this cycle, the work reported here focuses on identifying users whose postings demonstrate a high deletion rate with a presumption that the bad content is an indication of a struggling student rather than a malicious user. In this work, experiments are conducted on a large student-oriented online CQA community to understand struggling students' behaviors. A framework is proposed to find these users based solely on their activities. Finally, community feedback (i.e. human judgment) such as moderator evaluation or community votes for good content is used to detect these users in the early stages of their respective struggles. To evaluate this framework, we used data from Brainly, a large educational CQA service that is used in two different markets with more than 3.7 million users and 10.7 million answers. The results show that the human judgment feature identifies early-stage struggling users with high accuracy. Identifying these struggling users (students) could help educators to determine suitable ways to help their students instead of presuming them to be bad users and cutting them off from the community.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {165–174},
numpages = {10},
keywords = {education, community question-answering (cqa), struggling user, features},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020185,
author = {Novin, Alamir and Meyers, Eric},
title = {Making Sense of Conflicting Science Information: Exploring Bias in the Search Engine Result Page},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020185},
doi = {10.1145/3020165.3020185},
abstract = {Currently, there is widespread media coverage about the problems with 'fake news' that appears in social media, but the effects of biased information that appears in search engine results is also increasing. The authors argue that the search engine results page (SERP) exposes three important types of bias: source bias, algorithmic bias, and cognitive bias. To explore the relationship between these three types of bias, we conducted a mixed methods study with sixty participants (plus fourteen in a pilot to make a total of seventy-four participants). Within a library setting, participants were provided with mock search engine pages that presented order-controlled sources on a science controversy. Participants were then asked to rank the sources' usefulness and then summarize the controversy. We found that participants ranked the usefulness of sources depending on its presentation within a SERP. In turn, this also influenced how the participants summarized the topic. We attribute the differences in the participants' writings to the cognitive biases that affect a user's judgment when selecting sources on a SERP. We identify four main cognitive biases that a SERP can evoke in students: Priming, Anchoring, Framing, and the Availability Heuristic. While policing information quality is a quixotic task, changes can be made to both SERPs and a user's decision-making when selecting sources. As bias emerges both on the system side and the user side of search, we suggest a two-fold solution is required to address these challenges.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {175–184},
numpages = {10},
keywords = {document genre, document order, biases, bias, search engine results page, heuristics, serp},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020166,
author = {O'Brien, Heather and McKay, Jocelyn and Vangeest, Jacob},
title = {Learning From the News: The Role of Topic, Multimedia and Interest in Knowledge Retention},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020166},
doi = {10.1145/3020165.3020166},
abstract = {We conducted a study to examine how people interact with and learn from human-interest news stories. Participants engaged with news stories and completed knowledge retention tests to evaluate their ability to remember the content. We analyzed how the stories and the way in which they were presented (audio, video, text) related to knowledge retention. Results demonstrated a complex interaction between topic and knowledge retention, where participants obtained higher scores for the least preferred story. We explored these findings with respect to participants' demographics and user experience.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {185–193},
numpages = {9},
keywords = {online news, multimedia, learning, information interaction},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020189,
author = {Bota, Horatiu and Bennett, Paul N. and Awadallah, Ahmed Hassan and Dumais, Susan T.},
title = {Self-Es: The Role of Emails-to-Self in Personal Information Management},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020189},
doi = {10.1145/3020165.3020189},
abstract = {Email has been central to online communication for the past two decades. Through constant use, new information flows are being defined around users' interactions with emails. Alongside traditional messages, the email inbox is an always-available repository of to-do lists, reminders, files and notes. In this paper, we investigate the use of self-addressed emails (self-Es) as an information management tool, by analysing both: (i) responses to a survey about email use; and (ii) a collection of user donated self-addressed emails. Our results show that sending self-Es is a frequent behaviour among the users we questioned. In addition, we find that to-dos and reminders are the most popular type of information contained in emails-to-self. Our findings have direct implications for the development of systems that support novel interactions with information flows centred around email.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {205–214},
numpages = {10},
keywords = {personal information management, email search},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020175,
author = {Narang, Kanika and Dumais, Susan T. and Craswell, Nick and Liebling, Dan and Ai, Qingyao},
title = {Large-Scale Analysis of Email Search and Organizational Strategies},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020175},
doi = {10.1145/3020165.3020175},
abstract = {Email continues to be an important form of communication as well as a way to manage tasks and archive personal information. As the volume of email grows, organizing and finding relevant email remains challenging. In this paper, we present a large-scale log analysis of the activities that people perform on email mes-sages (accessing external information via links or attachments, responding to messages, and organizing messages), their search behavior, and their organizational practices in a popular web email client.First, we characterize general email activities as well as activities associated with search. We find that within search sessions, peo-ple are more likely to access information and respond to messag-es but less likely to organize. Second, we examine the relation-ship between characteristics of a person's mailbox and their search and organizational practices. People with larger mailboxes tend to organize more, respond a little more, and access infor-mation less. People with larger mailboxes and folder structures search more, but the number of folders has less influence on search. Third, we extend previous work on email organization (e.g., filers vs. pilers; cleaners vs. keepers) by examining the extent to which these strategies are evident in our large-scale analysis and influence email activities and search. People who rely heavily on one organizational strategy tend to use others less. People who organize less tend to search more. Finally, we de-scribe how these insights can influence the design of email search.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {215–223},
numpages = {9},
keywords = {email management strategies, email search},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020172,
author = {Htun, Nyi Nyi and Halvey, Martin and Baillie, Lynne},
title = {An Interface for Supporting Asynchronous Multi-Level Collaborative Information Retrieval},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020172},
doi = {10.1145/3020165.3020172},
abstract = {A great deal of research into Collaborative Information Retrieval (CIR) has assumed that search team members have the same level of unrestricted access to information. However, case studies and observations from different domains including government, healthcare and legal, have suggested that CIR sometimes involves people with unequal access to information. This type of scenario has been referred to as Multi-Level CIR (MLCIR). In addition to supporting collaboration, MLCIR systems must ensure that there is no unintended disclosure of sensitive information, this is an under investigated area of research. In this paper we present results of an evaluation of an interface we have designed for MLCIR scenarios. Pairs of participants used the interface under 3 different information access scenarios for a variety of search tasks. These scenarios included 1 CIR and 2 MLCIR scenarios, namely: full access (FA), document removal (DR) and term blacklisting (TR). Design interviews were conducted post evaluation to obtain qualitative feedback from participants. Evaluation results showed that our interface performed well for both DR and FA scenarios but for TR, team members with less access had a negative influence on their partner's search performance, demonstrating insights into how different MLCIR scenarios should be supported. Design interview results showed that our interface helped the participants to reformulate their queries, understand their partner's performance, reduce duplicated work and review their team's search history without disclosing sensitive information.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {225–234},
numpages = {10},
keywords = {interface design, asynchronous collaboration, non-uniform access, information retrieval, information access},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3020171,
author = {Htun, Nyi Nyi and Halvey, Martin and Baillie, Lynne},
title = {How Can We Better Support Users with Non-Uniform Information Access in Collaborative Information Retrieval?},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3020171},
doi = {10.1145/3020165.3020171},
abstract = {The majority of research in Collaborative Information Retrieval (CIR) has assumed that collaborating team members have uniform information access. However, practice and research has shown that there may not always be uniform information access among team members, e.g. in healthcare, government, etc. To the best of our knowledge, there has not been a controlled user evaluation to measure the impact of non-uniform information access on CIR outcomes. To address this shortcoming, we conducted a controlled user evaluation using 2 non-uniform access scenarios (document removal and term blacklisting) and 1 full and uniform access scenario. Following this, a design interview was undertaken to provide interface design suggestions. Evaluation results show that neither of the 2 non-uniform access scenarios had a significant negative impact on collaborative and individual search outcomes. Design interview results suggested that awareness of team's query history and intersecting viewed/judged documents could potentially help users share their expertise without disclosing sensitive information. Based on our results we provide important design recommendations to better support users with non-uniform information access in CIR.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {235–244},
numpages = {10},
keywords = {non-uniform access, collaborative information retrieval, multi-level collaboration, interface design, information access},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022125,
author = {Inthiran, Anushia},
title = {Information Sharing and Search Collaboration Activities of Health Consumers in South East Asia},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022125},
doi = {10.1145/3020165.3022125},
abstract = {Searching for health information is an activity conducted by people from all walks of life. Performing a health search is not a trivial task. A searcher could be overwhelmed by the sheer amount of information available and the need to understand technical and complex details. Performing a health search collaboratively could increase search efficacy. Sharing health information would encourage discourse. Health search collaboration and information sharing activities in developed countries have been analyzed. However, similar information is not available for health consumers from developing countries. In this work in progress paper, we describe search collaboration and information sharing activities of health consumers in South East Asia.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {245–248},
numpages = {4},
keywords = {sharing, collaboration, online, health, consumers, south east asia},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022126,
author = {Fu, Hengyi},
title = {Query Reformulation Patterns of Mixed Language Queries in Different Search Intents},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022126},
doi = {10.1145/3020165.3022126},
abstract = {With the increasing number of multilingual resources on the Internet, cross-language information retrieval has become an important research topic. In cultures where people speak both Chinese and English, using mixed language in oral speaking and web searching is a common phenomenon. While queries are the key element of information retrieval process, mixed-language queries have not yet been adequately studied. This study use query log analysis to examine the query reformulation patterns regarding Chinese-English mixed language queries, and how search intents may affect the query reformulation types users employ. The results can inform IR system designers to enhance cross-language controlled vocabularies and develop discovery platforms for multilingual content, and improve search engines to provide users with more relevant, personalized search results. The findings could also be expanded to other language combinations that would improve search engine designs.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {249–252},
numpages = {4},
keywords = {query reformulation, cross-language information retrieval, query log analysis, mixed language queries, search intents},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022127,
author = {Verberne, Suzan and van den Bosch, Antal and Wubben, Sander and Krahmer, Emiel},
title = {Automatic Summarization of Domain-Specific Forum Threads: Collecting Reference Data},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022127},
doi = {10.1145/3020165.3022127},
abstract = {We create and analyze two sets of reference summaries for discussion threads on a patient support forum: expert summaries and crowdsourced, non-expert summaries. Ideally, reference summaries for discussion forum threads are created by expert members of the forum community. When there are few or no expert members available, crowdsourcing the reference summaries is an alternative. In this paper we investigate whether domain-specific forum data requires the hiring of domain experts for creating reference summaries. We analyze the inter-rater agreement for both data-sets and we train summarization models using the two types of reference summaries. The inter-rater agreement in crowdsourced reference summaries is low, close to random, while domain experts achieve a considerably higher, fair, agreement. The trained models however are similar to each other. We conclude that it is possible to train an extractive summarization model on crowdsourced data that is similar to an expert model, even if the inter-rater agreement for the crowdsourced data is low.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {253–256},
numpages = {4},
keywords = {summarization, discussion forums, reference data},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022124,
author = {Kumpulainen, Sanna W. and Kautonen, Heli},
title = {Accidentally Successful Searching: Users' Perceptions of a Digital Library},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022124},
doi = {10.1145/3020165.3022124},
abstract = {People usually search information by using queries that are targeted to match the wording of the documents in the collections. However, during their search processes they may discover some useful pieces of information they did not expect. Serendipitous searching occurs when people search for information, but during their search process discover unexpected results. One key aspect of serendipity is chance encountering, which means the accidental and unexpected encountering with useful information. In this paper we address to the chance encounters, search success and search interests of information seekers using a national digital library called Finna. This study shows that chance encountering and search success increase with user satisfaction and that digital libraries can support information encountering.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {257–260},
numpages = {4},
keywords = {user survey, chance encounters, information encountering, user satisfaction},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022128,
author = {Zengin, Mustafa and Carterette, Ben},
title = {User Click Detection in Ideal Sessions},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022128},
doi = {10.1145/3020165.3022128},
abstract = {Users interact with search engine result pages in various ways, including their clicks, cursor movements, and page scrolls. Researchers model such user interaction behavior in order to understand users and improve search result presentation. In this paper we propose nine different user click models that take various real life search behavior into account. Our main assumption is that users base their clicks primarily on features of document titles, URLs, and snippets over the entire results page, as well as the queries submitted to the search engine and the documents seen previously in their session history. We evaluate our click models by their effectiveness at predicting actual user clicks using standard classification evaluation measures precision, recall, and area under the ROC curve (AUC). We show that incorporating information about the entire results page gives nearly 40% improvement in precision, and including information about the session history along with it increases precision by up to 43%.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {261–264},
numpages = {4},
keywords = {users, simulation, detection, clicks},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022129,
author = {Vu, Thanh and Willis, Alistair and Kruschwitz, Udo and Song, Dawei},
title = {Personalised Query Suggestion for Intranet Search with Temporal User Profiling},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022129},
doi = {10.1145/3020165.3022129},
abstract = {Recent research has shown the usefulness of using collective user interaction data (e.g., query logs) to recommend query modification suggestions for Intranet search. However, most of the query suggestion approaches for Intranet search follow an ``one size fits all'' strategy, whereby different users who submit an identical query would get the same query suggestion list. This is problematic, as even with the same query, different users may have different topics of interest, which may change over time in response to the user's interaction with the system.We address the problem by proposing a personalised query suggestion framework for Intranet search. For each search session, we construct two temporal user profiles: a click user profile using the user's clicked documents and a query user profile using the user's submitted queries. We then use the two profiles to re-rank the non-personalised query suggestion list returned by a state-of-the-art query suggestion method for Intranet search. Experimental results on a large-scale query logs collection show that our personalised framework significantly improves the quality of suggested queries.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {265–268},
numpages = {4},
keywords = {temporal user profiles, interactive ir, intranet search, learning to rank, personalised query suggestion},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022130,
author = {Jachja, Tiffany and Douglas, Oard W.},
title = {Goal-Directed Information Seeking in Time-Synchronized and Topic-Linked Records of the Apollo Lunar Missions},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022130},
doi = {10.1145/3020165.3022130},
abstract = {We live in an era in which ubiquitous networks bring together information from a vast array of sources. The resulting confluence creates new opportunities for providing integrated access. This paper describes the use of a system for exploring the rich recorded legacy of the Apollo missions to the Moon, using the event structure of each mission as an organizing principle. Qualitative analysis of a study with five journalism students indicates that the system is capable of supporting goal-directed information seeking},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {269–272},
numpages = {4},
keywords = {topic-linking, user study, time synchronization, content linking, apollo archive explorer},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022131,
author = {Low, Thomas and Bubalo, Nikola and Gossen, Tatiana and Kotzyba, Michael and Brechmann, Andr\'{e} and Huckauf, Anke and N\"{u}rnberger, Andreas},
title = {Towards Identifying User Intentions in Exploratory Search Using Gaze and Pupil Tracking},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022131},
doi = {10.1145/3020165.3022131},
abstract = {Exploration in large multimedia collections is challenging because the user often navigates into misleading directions or information areas. The vision of our project is to develop an assistive technology that is able to support the individual user and enhance the efficiency of an ongoing exploratory search. Such a technical search aid should be able to find out about the user's current interests and goals. Respective parameters can be found in the central and in the peripheral nervous system as well as in overt behavior. Therefore, we aim at using eye movements, pupillometry and EEG to assess respective information. Here, we describe the set-up and the first results of a preliminary user study investigating the effects of searching an image collection on eye movements and pupil dilations. First data show that numbers of fixation, fixation durations as well as pupil dilations differ systematically when looking at a subsequently selected target as compared with not selected items. These results support our vision that further research additionally investigating EEG can in fact result in better predicting the searchers goals and next choices.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {273–276},
numpages = {4},
keywords = {pupillometry, multimedia retrieval, exploratory search, gaze tracking},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022132,
author = {Waugh, Shermaine and McKay, Dana and Makri, Stephann},
title = { 'Too Much Serendipity': The Tension between Information Seeking and Encountering at the Library Shelves},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022132},
doi = {10.1145/3020165.3022132},
abstract = {The physical library shelves are regularly the site of serendipitous information discoveries, and are often sought out for this purpose. However, while some drawbacks to the shelves as information gateways have been documented, none to our knowledge relate to their capacity for facilitating serendipity. We present findings from a qualitative study of serendipity at the library shelves. This study uncovered a new drawback that we term the "seeking-encountering tension". On one hand, this tension entices people towards the relatively high-risk, high-reward activity of exploring new information avenues discovered serendipitously and, on the other, draws them back towards the relative safety of goal-directed information-seeking. We discuss some of the factors that contribute to this tension, and provide design suggestions for mitigating it. Understanding this tension can inform the design of physical and digital information environments that provide users the agency to switch between more and less focused information-seeking at will.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {277–280},
numpages = {4},
keywords = {serendipity, information seeking, information encountering, library shelves, browsing},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022133,
author = {Brazier, David and Harvey, Morgan},
title = {Strangers in a Strange Land: A Study of Second Language Speakers Searching for e-Services},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022133},
doi = {10.1145/3020165.3022133},
abstract = {While the recent trend of digitisation of government and related services offers many advantages, it could introduce problems for those who are less information literate or who have particular issues searching for and understanding the necessary content. In this study ten participants, who speak English as a second language, were given four search tasks designed to reflect actual information seeking situations. They completed pre- and post-search questionnaires to identify the relevancy of the task, their English language ability and search experience.Our results suggest that, despite a perception that they performed to the best of their abilities, were bookmarking relevant documents and that the given tasks were easy, the students were actually often choosing documents that are only partially or tangentially relevant. The repercussions of this discrepancy are clear and suggest that much more assistance is needed before such services can be made 'digital by default'.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {281–284},
numpages = {4},
keywords = {search, information behaviour, user studies, e-services, information literacy},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022134,
author = {MacFarlane, Andrew and Buchanan, George and Al-Wabil, Areej and Andrienko, Gennady and Andrienko, Natalia},
title = {Visual Analysis of Dyslexia on Search},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022134},
doi = {10.1145/3020165.3022134},
abstract = {A key problem in the field of search interfaces is dyslexic users interaction with the UI. Dyslexia is a widespread specific learning difficult (SpLD) (10% of any population is estimated to have this cognitive disability) which is under researched in the field of information retrieval. The focus here is an analysis of the User Interface (UI) for search, using visual analytical methods on eye tracking data to examine the difference between control and dyslexic searchers. We use a number of visual analytic methods including path similarity analysis (PSA) and clustering of time intervals to demonstrate both similarities and differences between the user groups. Observations of videos are used to augment the visualizations. Results demonstrate a clear difference between the user groups, and a clear memory effect on the user of search interfaces is shown -- this is a key contribution of this paper. We examine the results using of theories of dyslexia, contributing also to the field of dyslexia and search.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {285–288},
numpages = {4},
keywords = {dyslexia., visual analysis, information retrieval},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022135,
author = {Sanchiz, Myl\`{e}ne and Chevalier, Aline and Fu, Wai-Tat and Amadieu, Franck},
title = {Relationships between Age, Domain Knowledge and Prior Knowledge Pre-Activation on Information Searching},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022135},
doi = {10.1145/3020165.3022135},
abstract = {This study investigated the effects of age, prior domain knowledge and prior knowledge semantic pre-activation task on information searching. Results showed that the age-related differences were observed for the fantastic movies domain (for which older adults had significantly lower prior knowledge), whereas the effects of age were not replicated in the health domain (for which older adults had equal knowledge with young adults?). Semantic pre-activation of prior knowledge in the health domain was correlated to more analytic strategies when processing the search engine pages and when navigating.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {289–292},
numpages = {4},
keywords = {information searching, prior knowledge activation, web navigation., aging, domain knowledge},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022136,
author = {Harvey, Morgan and Pointon, Matthew},
title = {Perceptions of the Effect of Fragmented Attention on Mobile Web Search Tasks},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022136},
doi = {10.1145/3020165.3022136},
abstract = {Mobile devices are rapidly becoming our main method of accessing the Internet and are frequently used to perform on-the-go search tasks. The use of such devices in situations where attention must be divided, such as when walking, are common and research suggests that this increases cognitive load and, therefore, may have an impact on performance.In this work we conducted a laboratory experiment with both phone and tablet devices with the aim of evaluating common mobile situations that cause; fragmented attention, impact search performance and impact on user perception. To do this the distraction level was varied by simulating 3 everyday situations: 1) walking quickly (on a treadmill), 2) navigating a pre-defined route and 3) sitting still (which was used as the baseline condition). The results showed that different experimental conditions had a number of different effects on the participants' perceptions of their own search performance, how hurried they felt and how engaged they were in the tasks.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {293–296},
numpages = {4},
keywords = {mobile search, cognition, experimentation, search experience, user study, fragmented attention},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022137,
author = {Aigner, Johannes and Durchardt, Amelie and Kersting, Thiemo and Kattenbeck, Markus and Elsweiler, David},
title = {Manipulating the Perception of Credibility in Refugee Related Social Media Posts},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022137},
doi = {10.1145/3020165.3022137},
abstract = {This paper describes a controlled web-based study (n=126), investigating whether the perception of the credibility of refugee-related Tweets can be influenced by cues already reported in the literature for social media content generally. We provide empirical evidence that both a Tweet's popularity and the presence of links -- even neutral links created by URL shortening services -- may increase a user's belief that the Tweet contains credible information. This is important because the propagation of false information relating to refugees on social media sites has been well documented.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {297–300},
numpages = {4},
keywords = {false information, perception of information, social media, rumours},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022138,
author = {Seifert, Christin and Mitschick, Annett and Schl\"{o}tterer, J\"{o}rg and Dachselt, Raimund},
title = {Focus Paragraph Detection for Online Zero-Effort Queries: Lessons Learned from Eye-Tracking Data},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022138},
doi = {10.1145/3020165.3022138},
abstract = {In order to realize zero-effort retrieval in a web-context, it is crucial to identify the part of the web page the user is focusing on. In this paper, we investigate the identification of focus paragraphs in web pages. Starting from a naive baseline for paragraph and focus paragraph detection, we conducted an eye-tracking study to evaluate the most promising features. We found that single features (mouse position, paragraph position, mouse activity) are less predictive for gaze which confirms findings from other studies. The results indicate that an algorithm for focus paragraph detection needs to incorporate a weighted combination of those features as well as additional features, e.g. semantic context derived from the user's web history.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {301–304},
numpages = {4},
keywords = {focus paragraph detection, zero-effort queries, eye tracking},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022139,
author = {Melgar, Liliana and Koolen, Marijn and Huurdeman, Hugo and Blom, Jaap},
title = {A Process Model of Scholarly Media Annotation},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022139},
doi = {10.1145/3020165.3022139},
abstract = {Annotation has been identified as one of the "scholarly primitives", and plays a pivotal role in facilitating access to audio-visual (AV) media in a scholarly context. However, there is a lack of understanding of scholars' annotation needs and behavior. This paper is part of a group of studies aiming to understand how to improve annotation support of AV media, in order to facilitate research activities of media scholars and other scholars who make intensive use of AV media.The main findings confirm previous research discerning stages in media scholars' research processes, and indicate a great variety of research activities which occur in a non-linear order. Our studies also show that different annotation activities occur along those stages. The main contribution of this paper is a generic process model capturing AV media annotation, potentially applicable to a variety of research use cases in a scholarly context.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {305–308},
numpages = {4},
keywords = {audio-visual media research, time-based media, video annotation},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022140,
author = {Thiel, Marcus and Ludwig, Philipp and Mossakowski, Till and Neuhaus, Fabian and N\"{u}rnberger, Andreas},
title = {Web-Retrieval Supported Argument Space Exploration},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022140},
doi = {10.1145/3020165.3022140},
abstract = {Solid decision making should be ideally based on clear arguments that can be justified by trustworthy information sources. However, argument spaces can quickly get quite complex and it is very often hard to trace the line of arguments found in literature or social media such as blogs and forums. In this paper, we propose a framework for a decision supporting interactive information retrieval system using methods for argument exploration based on textual documents. This concept is supported by a prototype that focuses on the actual analysis of the retrieved arguments in order to obtain a justified decision. For that we use a simplified argumentation graph with nodes as arguments and simple attacking and supporting relations. A web-based plausibility value is propagated (using ranked-based argumentation semantics) through the network for estimating the quality of the arguments. This is based on a web search for documents that support these arguments. The final decision can further be supported by chosing certain preferred interpretations of an abstract dialectical framework, leading to an integrated view of searching, creating, analysing and deciding.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {309–312},
numpages = {4},
keywords = {graph exploration, argument exploration, interactive argument exploration, rank-based semantics, argument retrieval},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022141,
author = {Medlar, Alan and Glowacka, Dorota},
title = {Using Topic Models to Assess Document Relevance in Exploratory Search User Studies},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022141},
doi = {10.1145/3020165.3022141},
abstract = {Evaluation is crucial in assessing the effectiveness of new information retrieval and human computer interaction techniques and systems. Relevance judgements are often performed by humans, which makes obtaining them expensive and time consuming. Consequently, relevance judgements are usually performed only on a subset of a given collection of data or experimental results with a focus on the top ranked documents. However, when assessing the performance of exploratory search systems, the diversity or subjective relevance of documents that the user was presented with over a search session are often of more importance than the relative ranking of top documents. In order to perform these types of assessment, all the documents in a given collection need to be judged for relevance. In this paper, we propose an approach based on topic modeling that can greatly accelerate document relevance judgment of an entire document collection with an expert assessor needing to mark only a small subset of documents from a given collection. Experimental results show a substantial overlap between relevance judgments compared to a human assessor.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {313–316},
numpages = {4},
keywords = {topic models, user studies, exploratory search, relevance assessment},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022142,
author = {Ishita, Emi and Miyata, Yosuke and Ueda, Shuichi and Kurata, Keiko},
title = {A Structural Equation Model of Information Retrieval Skills},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022142},
doi = {10.1145/3020165.3022142},
abstract = {Identifying factors that influence information retrieval skills can help us to understand search behavior and show what skills are required to conduct efficient and accurate searches. This paper describes a study in which relationship factors that influence the information retrieval skills of a cohort of 1,551 Japanese Internet users are investigated using a combination of survey methods, factor analysis, and structural equation modeling. Our factor analysis confirms the importance of three sub-skill groups that are similar to sub-skill groups that have been previously reported (i.e., formal Internet skills, operational skills, and assessment skills) and indicates the importance of a fourth group (which we call "search strategy skills"). Our structural equation model incorporates two novel factors that have not previously been studied in this context: critical thinking ability, and self-efficacy for the Internet and information retrieval. The results show that critical thinking ability and self-efficacy positively influence the information retrieval skill level, and age is found to be a negative influence. Contrary to previously reported results, little independent effect is seen from educational attainment.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {317–320},
numpages = {4},
keywords = {structural equation model., self-efficacy for the internet and information retrieval, information retrieval skills, critical thinking ability},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022143,
author = {Husev\r{a}g, Anne-Stine Ruud},
title = {Categorization of Known-Item Search Terms in a TV Archive},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022143},
doi = {10.1145/3020165.3022143},
abstract = {This paper reports on a preliminary explorative study that categorizes search terms provided by 50 users after having watched short clips from TV programs from The Norwegian Broadcasting Corporation archive. The aim of this study is to improve indexing by gaining knowledge about users preferred search terms. One clip is from a news program, and two clips come from a literature program. The search terms are categorized according to The Panofsky-Shatford mode/facet matrix. The study shows that specific search terms like named entities are used the most for both genres, and that generic and abstract terms are more important in the literature clips than the news clip. The search terms provided by users were matched with text from the subtitles from the clip, and the results showed that 17%, 32% and 40% of the terms were found for literature clip 1, literature clip 2 and news clip respectively. The percentage was higher when the terms were matched with subtitles from the whole program, and would have been even higher if additional on-screen text was included.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {321–324},
numpages = {4},
keywords = {metadata, search term categorization, multimedia indexing},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022144,
author = {Trippas, Johanne R. and Spina, Damiano and Cavedon, Lawrence and Sanderson, Mark},
title = {How Do People Interact in Conversational Speech-Only Search Tasks: A Preliminary Analysis},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022144},
doi = {10.1145/3020165.3022144},
abstract = {We present preliminary findings from a study of mixed initiative conversational behaviour for informational search in an acoustic setting. The aim of the observational study is to reveal insights into how users would conduct searches over voice where a screen is absent but where users are able to converse interactively with the search system. We conducted alaboratory-based observational study of 13 pairs of participants each completing three search tasks with different cognitive complexity levels. The communication between the pairs was analyzed for interaction patterns used in the search process. This setup mimics the situation of a user interacting with a search system via a speech-only interface.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {325–328},
numpages = {4},
keywords = {observational study, thematic analysis, response generating, interaction themes, spoken conversational search, speech-only communication channel, voice search, empirical study},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022145,
author = {Rath, Manasa and Le, Long T. and Shah, Chirag},
title = {Discerning the Quality of Questions in Educational Q&Ausing Textual Features},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022145},
doi = {10.1145/3020165.3022145},
abstract = {In an information seeking episode, attributes such as relevance, quality, and the nature of the information sought/obtained are directly related to the nature and the quality of the query or question that represents an information need. It is, therefore, imperative that we identify potential problems with such representation to make the information seeking outcome and the experience more successful. In this paper, we investigate the question quality for the educational community question answering (CQA) site Brainly by examining 2,000 questions, of which 1,000 were answered and 1,000 were unanswered. Two human assessors rated the quality of each question on a scale from 1-5 based on factors such as ambiguity, poor syntax, lack of information, complexity, inappropriateness, and inconsistency. We then identified different textual features that are needed to detect question quality. A logistic regression classifier was built to categorize question features based on the rating scale and textual features present in the question. The results show higher ROC curves for ambiguity, lack of information, inappropriateness, complexity and excessive information; and lower ROC values for poor syntax and inconsistency among the questions. The findings demonstrate that the classifier failed to perform when faced with ill-framed or inconsistent phrases in a question. The work described here presents a method for identifying high and low-quality questions, the knowledge of which could be instrumental in helping reformulate users' questions and present them to a system or a community for more successful processes and outcomes.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {329–332},
numpages = {4},
keywords = {question quality, logistic regression, machine learning, community q&a},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022146,
author = {Liu, Chang and Liu, Jiqun and Wei, Yiming},
title = {Scroll up or down? Using Wheel Activity as an Indicator of Browsing Strategy across Different Contextual Factors},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022146},
doi = {10.1145/3020165.3022146},
abstract = {This study used wheel activity as an indicator of users' browsing strategy, and explored the effects of various contextual factors on users' browsing patterns. Users' wheel activities were extracted from a search log in a user experiment, in which forty participants with different backgrounds conducted an online search in various contexts. To statistically test the potential effects of contexts on browsing strategy, we calculated three types of scroll-based variables to capture different types of browsing behaviors, and analyzed the effects of contextual factors via OLS regression analysis. Our results revealed that information understanding type tasks might lead to more proportion of revisit browsing range, while higher pressure level and higher pre-familiarity might lead to larger one-time browsing range; however, time constraint did not influence their browsing strategies. Our study also provided methodological implication for future interactive information retrieval studies by testifying and highlighting the usefulness of users' wheel activities in depicting online browsing patterns.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {333–336},
numpages = {4},
keywords = {browsing behavior, page type, task facet, wheel activity},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022147,
author = {B\"{o}schen, Falk and Strobel, Benjamin and Goos, Steffen and Liebers, Christoph and Rathje, Bastian and Scherp, Ansgar},
title = {Evaluation of the Comprehensiveness of Bar Charts with and without Stacking Functionality Using Eye-Tracking},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022147},
doi = {10.1145/3020165.3022147},
abstract = {Bar charts are widely used to visualize core results of experiments in research papers or display statistics in news, media, and other reports. However, visualizations like bar charts are mostly manually designed, static presentations of data without the option of adaption to a user's needs. But so far, it is unknown whether interactivity improves the understanding of charts. In this work, we compare static with dynamic bar charts, which offer an interactive stacking option. We assess the efficiency, effectiveness, and satisfaction when answering questions regarding the content of a bar chart. An eye-tracker is used to measure the efficiency. We have conducted a between group experiment with 38 participants. While one group had to solve the aggregation tasks using stackable, i.e., interactive bar charts, the other group was limited to static visualizations. Even though new interactive features require familiarization, we found that the stacking feature significantly helps completing the tasks with respect to efficiency, effectiveness, and satisfaction for bar charts of varying complexity.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {337–340},
numpages = {4},
keywords = {interactive bar charts, eye-tracking, user study, stacking},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022148,
author = {Gwizdka, Jacek},
title = {I Can and So I Search More: Effects Of Memory Span On Search Behavior},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022148},
doi = {10.1145/3020165.3022148},
abstract = {Search effort is an important aspect of Interactive Information Retrieval (IIR). Prior findings show that higher cognitive ability searchers tend to perform more actions than lower ability searchers. In an eye-tracking lab study we investigated the effects of working memory (WM) on search effort. The findings show that higher WM searchers perform more actions and that most significant differences are in time spent on reading results pages. We also show that behavior of high and low WM searchers changes differently in the course of a search task performance.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {341–344},
numpages = {4},
keywords = {eye-tracking, working memory span., mental effort, web search},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022149,
author = {Braslavski, Pavel and Savenkov, Denis and Agichtein, Eugene and Dubatovka, Alina},
title = {What Do You Mean Exactly? Analyzing Clarification Questions in CQA},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022149},
doi = {10.1145/3020165.3022149},
abstract = {Search as a dialogue is an emerging paradigm that is fueled by the proliferation of mobile devices and technological advances, e.g. in speech recognition and natural language processing. Such an interface allows search systems to engage in a dialogue with users aimed at fulfilling their information needs. One key capability required to make such search dialogues effective is asking clarification questions (CLARQ) proactively, when a user's intent is not clear, which could help the system provide more useful responses. With this in mind, we explore the dialogues between the users on a community question answering (CQA) website as a rich repository of information-seeking interactions. In particular, we study the clarification questions asked by CQA users in two different domains, analyze their behavior, and the types of clarification questions asked. Our results suggest that the types of CLARQ are very diverse, while the questions themselves tend to be specific and require both domain- and general knowledge. However, focusing on popular CLARQ types and domains can be fruitful. As a first step towards automatic generation of clarification questions, we explore the problem of predicting the specific subject of a clarification question. Our findings can be useful for future improvements of intelligent dialog search and question answering systems.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {345–348},
numpages = {4},
keywords = {qa, question answering, dialog systems, conversational answer retrieval, cqa, community qa, interactive qa},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022150,
author = {Crescenzi, Anita and Capra, Robert and Arguello, Jaime},
title = {Time Limits, Information Search and the Use of Search Assistance},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022150},
doi = {10.1145/3020165.3022150},
abstract = {In this paper, we analyze the impact of task time limits as described by 24 participants in an experimental study investigating the use of a search assistance tool, the Search Guide (SG), during four search tasks with varying levels of cognitive complexity. Participants were given a 12 minute task time limit and a warning notification when 3 minutes remained. In post-experiment interviews, participants reported two different impacts of the time limit on use of the SG: ten described using the SG as a way to save time given the time limit while five reported less SG use due to uncertainty whether it would contain useful information. Participants also described skimming and reading pages more shallowly, selecting easier to read search results, and bookmarking pages more freely because of the limited time they had to complete the task.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {349–352},
numpages = {4},
keywords = {search assistance, time limit, time constraint, information search, time pressure},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022151,
author = {Wang, Yiwei and Sarkar, Shawon and Shah, Chirag},
title = {Investigating Information Seekers' Selection of Interpersonal and Impersonal Sources},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022151},
doi = {10.1145/3020165.3022151},
abstract = {Information source selection is essential to individuals' information seeking behaviors. Existing studies have focused on the criteria seekers employ when choosing information sources, such as sources' accessibility and quality, as well as the contextual factors that shape a seeker's selection. However, existing findings are somewhat conflicting and lack in-depth understanding of the reasons behind individuals' choices. The study reported here invited 53 participants from diverse backgrounds to perform simulated information seeking tasks over a two-day period and to report their experiences and findings in an online logbook. Semi-structured interviews with 23 of them were also conducted in order to examine the issues that arose from the logbooks. Our preliminary findings present several factors associated with participants' choices between impersonal and interpersonal sources. While interpersonal sources are deemed to be more suitable in capturing the context of an information query and providing personalized information, impersonal sources are found to be more accessible under a time constraint while depicting no emotion towards sensitive issues.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {353–356},
numpages = {4},
keywords = {information seeking in context, information seeking, information seeking sources},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022152,
author = {Kitazawa, Takuya},
title = {Sketching Dynamic User-Item Interactions for Online Item Recommendation},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022152},
doi = {10.1145/3020165.3022152},
abstract = {Online recommendation techniques such as incremental matrix factorization have been widely studied to capture users' preferences from real-world dynamic user-item interactions. These recommenders generally take a model-based approach which relies on stochastic gradient descent optimization, but it sometimes shows difficulties on hyperparameter optimization and scalability. In order to work around this difficulty, the author considers a completely different approach based on matrix sketching, which is more mathematically tractable and flexible than the existing techniques. More specifically, this paper proposes a new online item recommender inspired by a matrix-sketching-based streaming anomaly detection framework. We discuss its fruitful properties with particular emphasis on the similarities between item recommendation and anomaly detection. Experimental results demonstrate robustness and flexibility of the proposed framework.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {357–360},
numpages = {4},
keywords = {online learning, implicit feedback, matrix sketching},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022153,
author = {Singh, Jaspreet and Anand, Avishek},
title = {Designing Search Tasks for Archive Search},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022153},
doi = {10.1145/3020165.3022153},
abstract = {Longitudinal corpora like legal, corporate and newspaper archives are of immense value to a variety of users, and time as an important factor strongly influences their search behavior in these archives. While many systems have been developed to support users' temporal information needs, questions remain over how users utilize these advances to satisfy their needs. Analyzing their search behavior will provide us with novel insights into search strategy, guide better interface and system design and highlight new problems for further research. In this paper we propose a set of search tasks, with varying complexity, that IIR researchers can utilize to study user search behavior in archives. We discuss how we created and refined these tasks as the result of a pilot study using a temporal search engine. We not only propose task descriptions but also pre and post-task evaluation mechanisms that can be employed for a large-scale study (crowdsourcing). Our initial findings show the viability of such tasks for investigating search behavior in archives.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {361–364},
numpages = {4},
keywords = {newspaper archive, histdiv, interactive ir, search task, timeline, news search},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022154,
author = {Arora, Piyush and Jones, Gareth J.F.},
title = {Identifying Useful and Important Information within Retrieved Documents},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022154},
doi = {10.1145/3020165.3022154},
abstract = {We describe an initial study into the identification of important and useful information units within documents retrieved by an information retrieval system in response to a user query created in response to an underlying information need. This study is part of a large investigation of the exploitation of useful and important units from retrieved documents to generate rich document surrogates to improve user search experience. We report three user studies using a crowdsourcing platform, where participants were first asked to read an information need and contents of a relevant document and then to perform actions depending on the type of study: i) write important information units (WIIU), ii) highlight important information units (HIIU) and iii) assess importance of already highlighted information units (AIHIU). Further, we discuss a novel mechanism of measuring similarities between content annotations. We find majority agreement of about 0.489 and pairwise agreement of 0.340 among users annotation in the AIHIU study, and average cosine similarity of 0.50 and 0.57 between participant annotations and documents in the WIIU and HIIU studies respectively.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {365–368},
numpages = {4},
keywords = {user studies, document annotations, effective snippet generation, identifying useful and important information units, document surrogates generation},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022155,
author = {Dehghani, Mostafa and Jagfeld, Glorianna and Azarbonyad, Hosein and Olieman, Alex and Kamps, Jaap and Marx, Maarten},
title = {Telling How to Narrow It Down: Browsing Path Recommendation for Exploratory Search},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022155},
doi = {10.1145/3020165.3022155},
abstract = {Supporting exploratory search tasks with the help of structured data is an effective way to go beyond keyword search, as it provides an overview of the data, enables users to zoom in on their intent, and provides assistance during their navigation trails. However, finding a good starting point for a search episode in the given structure can still pose a considerable challenge, as users tend to be unfamiliar with exact, complex hierarchical structure. Thus, providing lookahead clues can be of great help and allow users to make better decisions on their search trajectory.In this paper, we investigate the behaviour of users when a recommendation engine is employed along with the browsing tool in an exploratory search system. We make use of an exploratory search system that facilitates browsing by mapping the data on a hierarchical structure. We designed and developed a path recommendation engine as a feature for this system, which given a text query, ranks different browsing paths in the hierarchy based on their likelihood of covering relevant documents. We conduct a user study comparing the baseline system with the featured system.Our main findings are as follows: We observe that, using the baseline system the users tend to explore the data in a breadth-first-like approach by visiting different data points at the same level of abstraction to choose one of them to expand and go deeper. Conversely, with browsing path recommendation (BPR) as a feature, the users tend to drive their search in a more depth-first-like approach by quickly going deep into the data hierarchy. While the users still incline to explore different parts of the search space by using BPR, they are able to restrain or augment their search focus more quickly and access smaller but more promising regions of the data. Therefore, they can complete their tasks with less time and effort},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {369–372},
numpages = {4},
keywords = {bpr, recommendation, expose, exploratory search},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022156,
author = {Kulahcioglu, Tugba and Fradkin, Dmitriy and Palanivelu, Sridharan},
title = {Incorporating Task Analysis in the Design of a Tool for a Complex and Exploratory Search Task},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022156},
doi = {10.1145/3020165.3022156},
abstract = {Due to its nature, a complex and exploratory search task is not directly actionable; it needs to be decomposed into actionable sub-tasks. Achieving this decomposition is usually not trivial for non-expert users. Also, the users need additional support to decrease their cognitive workload, regardless of their experience level.A tool designed for a specific task should handle the above issues. In this paper, we present a design approach that can help achieve this, and exemplify this approach using the search task of patent infringement discovery. We apply hierarchical task analysis to analyze a successful goal decomposition scenario for the task. This kind of decomposition makes explicit the tasks that are most responsible for the cognitive workload of the user. We then apply cognitive analysis to reveal the knowledge that enables such decomposition. Finally, we use these findings to design the tool in a way that reduces the load on the user and enables achieving decomposition for non-expert users.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {373–376},
numpages = {4},
keywords = {complex and exploratory search, goal based decomposition, information retrieval, search tool design, requirements analysis},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022157,
author = {Gwizdka, Jacek and Bilal, Dania},
title = {Analysis of Children's Queries and Click Behavior on Ranked Results and Their Thought Processes in Google Search},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022157},
doi = {10.1145/3020165.3022157},
abstract = {We investigate query characteristics and click behavior on SERPs of children in grades 6 and 8 (ages 11 and 13, respectively). We employ Retrospective Think-Aloud (RTA) protocol to elicit children's thought processes while clicking on results and to identify the sources of information that shaped these processes. We analyze the effect of grade level and task type on query characteristics and click behavior. Early findings show statistical significance across the three tasks in relation to query characteristics and between younger and older children in relation to query entry duration, count of web pages visited and count of result pages clicked on in SERPs. Our study confirms findings reported in previous research, including large-scale search logs studies, and reveals new findings in some areas.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {377–380},
numpages = {4},
keywords = {thought processes., search engines, google, click-through, serps, children, query analysis, information search},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022158,
author = {Dodson, Samuel and Freund, Luanne and Kopak, Rick},
title = {Do Highlights Affect Comprehension? Lessons from a User Study},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022158},
doi = {10.1145/3020165.3022158},
abstract = {A largely unquestioned assumption in social reading is that publicly shared annotations improve reading outcomes. In this study, we explore the specific assumption that relevant and irrelevant passive highlighting affects comprehension. Participants were divided by cognitive style based on their degree of Field Dependence-Independence [20]. We found that irrelevant highlights had significant negative effects on reading comprehension for Field Independents (FIs), but not Field Dependents (FDs). This is a surprising result because FDs typically rely on external cues to structure and help process information, whereas FIs use internal cues. This suggests that highlighting cues information but does not structure it.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {381–384},
numpages = {4},
keywords = {highlighting, comprehension, social reading, reading, annotation},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022159,
author = {McKay, Dana and Buchanan, George R.},
title = {Slide Over Here: The Various Adjacencies of Co-Borrowed Ebooks},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022159},
doi = {10.1145/3020165.3022159},
abstract = {One of the major failings of ebook collections is the lack of readily available browsing mechanisms particularly in academic libraries. This stands in sharp contrast to the library shelves, and is bemoaned by readers as a reason to avoid the use of ebooks. Nonetheless earlier work has identified limited ebook co-borrowing; in this paper we address the relationships between these ebooks with a view to understanding how readers accessed them in a single session.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {385–388},
numpages = {4},
keywords = {libraries, information behaviour, information seeking, browsing, user studies},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022160,
author = {Hashemi, Seyyed Hadi and Kamps, Jaap},
title = {Skip or Stay: Users' Behavior in Dealing with Onsite Information Interaction Crowd-Bias},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022160},
doi = {10.1145/3020165.3022160},
abstract = {Mobile devices and the internet of things blend our virtual online behavior with our actions in the real-world. The physical context creates numerous external factors that play a role in the user's online interactions, thus creating new external biases in the collected information interaction logs. Our general aim is to improve our understanding of onsite users' behavior, which allow us to create better online and onsite contextual suggestion systems. We focus on the cultural heritage domain and have collected onsite users' information interaction logs of visits in a museum. This prompts the question: How to understand users' behavior in order to be able to predict their onsite behaviors? Our main findings are the following: First, users behave differently in different onsite contextual situations. Second, there is a significant dependency between users' onsite behaviors and other users, who are interacting with next point of interests (POIs). Third, we have proposed a contextual Skip-Or-Stay behavior classifier based on four different pairwise contextual features that significantly improves a defined baseline based on all the considered evaluation metrics. Fourth, we have analyzed the importance of different contexts in the Skip-or-Stay behavior predictions.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {389–392},
numpages = {4},
keywords = {internet of things, behavioral dynamics, onsite logs, bias},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022166,
author = {Husev\r{a}g, Anne-Stine Ruud},
title = {Exploring the Role of Named Entities in Automatic Indexing},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022166},
doi = {10.1145/3020165.3022166},
abstract = {Due to a major digitization effort, the Norwegian Broadcasting Corporation, NRK, has made Norwegian cultural heritage from the last century of radio and TV available to the public. It is impossible to manually go through and index all the digitized material, and automatic methods are required. This PhD project explores the possible role and usefulness of named entities in an automatic indexing process. This is done by annotating named entities in textual documents from NRK (textual description in metadata records and subtitles), analyzing differences in various genres and document types, and surveying potential users. Different methods for extracting the most salient named entities will be investigated. This project encompasses both multimedia indexing, information behavior and different forms of evaluation.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {393–394},
numpages = {2},
keywords = {metadata, multimedia indexing, named entities},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022167,
author = {Fardous, Jannatul and Du, Jia Tina and Choo, Kim-Kwang Raymond and Huang, Songshan (Sam)},
title = {Investigating Mobile Social Media Users? Behaviors in Tourism Collaborative Information Seeking},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022167},
doi = {10.1145/3020165.3022167},
abstract = {Leisure travelers most often travel in groups with family, relatives or friends. It is argued that tourist information search tends to be more collaborative than a completely individual decision-making exercise. Collaborative information seeking (CIS) deals with collaboration in searching for information. In recent years, social media has been steadily increasing as an important information source for tourists who access social media frequently through their mobile devices. Research has shown that travelers rely more on the suggestions and reviews provided by experienced tourists for their travel planning and decision-making. Tourists undertake social search during which they exploit their social networks/relationships to improve the search process. However, limited research has investigated social media users' behaviors in collaborative search for tourism information. What is the role of social media in supporting of collaborative tourism information search, including collaborative search patterns and strategies in social environments, has remained unknown. This research aims to investigate mobile social media users' behaviors in collaborative search for tourism information. Using the Grounded Theory approach, a conceptual framework of mobile social media users' tourism CIS behavior will be built. Semi-structured in-depth interviews will be employed to collect users' search experiences.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {395–397},
numpages = {3},
keywords = {collaborative information seeking (cis), social media, tourism.},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022168,
author = {Barifah, Maram Hassan},
title = {Automatic Simulation of Users for Interactive Information Retrieval},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022168},
doi = {10.1145/3020165.3022168},
abstract = {Hiring and engaging real users for conducting user studies is costly and time consuming. Therefore, simulating users has been proposed as a resource saving solution. Simulation helps to predict users' performance with retrieval systems and could provide researchers with much needed insights. There is a growing body of research in simulating users but most of the research conducted in the field is based only on data about how real users interact with the Information Retrieval System (IRS) leaving out aspects describing information seeking behaviours and individual differences. Consequently, essential data about users is not accounted thus the models are less realistic. To overcome this issue, an alternative approach is proposed. It concerns looking at user behaviour and analysing all the influencing factors that contribute to the user profile in order to produce representative user models. Thus, the aim of this research is to build real user profiles in order to produce more realistic user simulation. We will achieve that by capturing information seeking behaviour through user studies and selecting those factors and attributes that make our user models more realistic and operational at the same time. Furthermore, the proposed approach will allow to reduce the number of real users needed to evaluate the system.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {399–401},
numpages = {3},
keywords = {information seeking behaviour, simulation, evaluation, interactive information retrieval, user profile, persona},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022171,
author = {Karatassis, Ioannis},
title = {WebSAIL: Computer-Based Methods for Enhancing Web Search Literacy},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022171},
doi = {10.1145/3020165.3022171},
abstract = {Recent studies reveal that most Web search engine users lack of appropriate search strategies for finding information efficiently and effectively, and overestimate their capabilities in the domain of Web search. As a consequence these users spend more time in searching for information and also do not always find the best results. They eventually miss out on important information and may not even be aware of this fact, especially in more complex Web search tasks. Users get frustrated after failing at finding information they are looking for and abandon the search session at worst. We launched the WebSAIL project to tackle these deficits by promoting Web search literacy. Different methods (i.e., a tutorial, scaffolding, and gamification) will be used for training. In the end we will compare the applied methods to determine whether Web search literacy can be enhanced at all, whether acquired knowledge is long-lasting and which method has the biggest impact on the enhancement of Web search literacy.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {403–405},
numpages = {3},
keywords = {web search, scaffolding, tutorial, web search literacy, gamification, web search competence},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022172,
author = {Mitsui, Matthew Ryan},
title = {A Generative Framework to Query Recommendation and Evaluation},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022172},
doi = {10.1145/3020165.3022172},
abstract = {In practice, query recommenders in Web search typically recommend queries directly from a query log or iteratively refine a user's current context to make recommendations. These approaches either limit themselves to queries in the log or do not take necessary exploratory leaps in their recommendations. Moreover, they do not directly incorporate the encompassing, driving information needs and tasks. The author first shows that user queries may not necessarily be the best to use for recommendations and moreover proposes a framework for generating novel queries for query recommendation, using an approximation of need.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {407–409},
numpages = {3},
keywords = {query recommendation, diversity, user simulations, search session analysis},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022173,
author = {Ong, Kevin},
title = {Using Information Foraging Theory to Understand Search Behavior in Different Environments},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022173},
doi = {10.1145/3020165.3022173},
abstract = {The aim of this research proposal is to understand the extent in which Information Scent, part of Information Foraging Theory, influence the perception of relevance of retrieved search engine result pages (SERPs) in different environments (desktop and mobile). %We intend to study this influence by observing information seekers' behavior when they are searching for topics on a typical search engine. Firstly, we planned to investigate how previously found correlations between information scent and search behavior on desktop SERPs may also applicable on mobile. Secondly, we investigate if the differences in search behavior are also caused by SERP visibility and/or physical input behavior in different environments. Lastly, we would like to observe the extent in which changing snippet length can affect web search behavior. The perception of relevance on SERPs might be similar in both environments because the arrangement of SERPs on both mobile and desktop are identical; or different because the visibility of search results is less on mobile compared to desktop, due to limited screen sizes. We wanted to study the extent of which the physical limitations might significantly impact search behavior in different environments due to expected ``hidden scent". We conducted two user studies to observe these phenomenon and seek to understand search behavior by manipulating the SERPs presented to users. We observed both similarities and differences in web search behavior between the environments. On the desktop, increasing information scent led to lower positions of search results saved as relevant and lower positions of mouse hover. However, on mobile, increasing relevant search results beyond the initial screen size reduced number of documents examined.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {411–413},
numpages = {3},
keywords = {search strategies, search behavior, query reformulation, information foraging theory},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022174,
author = {Novin, Alamir},
title = {Missing Information in the Classroom and Misinformed by the Crowd: Developing Analytical Skills for Understanding Online Controversies},
year = {2017},
isbn = {9781450346771},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3020165.3022174},
doi = {10.1145/3020165.3022174},
abstract = {At the heart of this research is the role freedom of speech and freedom of access plays in the information era. Prior research found that while our access to information is rising, so is our level of spreading misinformation. This research will build on these prior studies to argue that our biases lead us to share less meaningful knowledge constructs. To tackle this problem this study integrates the fields of Human-Computer Interactions (to study our implicit biases), Social Network Analysis (to research the spread of biases), Information Visualization (to study the representation of bias) and Collaborative Information Behaviour (to observe the dialogical reconciliation of biases). The research will build on prior research to explore how students contextualize the various biases in the science controversies that they encounter online. Two objectives have been set to be accomplished by the end of this research: 1) develop a strategy for classrooms to equip students with skills for evaluating online science information and 2) develop recommendations for how online interfaces can present information that contextualizes conflicting information in a science controversy.},
booktitle = {Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval},
pages = {415–416},
numpages = {2},
keywords = {search engine results page, heuristics, biases, collaborative information behavior, document genre, serp, document order, bias, collaboration, collaborative information seeking},
location = {Oslo, Norway},
series = {CHIIR '17}
}

@inproceedings{10.1145/3020165.3022175,
author = {Brazier, David},
title = {The Long Term Effects of Search Query Examples on the Search Behaviours of Non

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repo_name: goyalkaraniit/acm-cr