text:
state-of-the-art systems, but only with a good composition function; context sensitivity improves performance and significantly reduces repetition.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {573–580},
numpages = {8},
keywords = {multi-document summarization, frequency, context-sensitivity, compositionality},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148270,
author = {Carberry, Sandra and Elzer, Stephanie and Demir, Seniz},
title = {Information Graphics: An Untapped Resource for Digital Libraries},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148270},
doi = {10.1145/1148170.1148270},
abstract = {Information graphics are non-pictorial graphics such as bar charts and line graphs that depict attributes of entities and relations among entities. Most information graphics appearing in popular media have a communicative goal or intended message; consequently, information graphics constitute a form of language. This paper argues that information graphics are a valuable knowledge resource that should be retrievable from a digital library and that such graphics should be taken into account when summarizing a multimodal document for subsequent indexing and retrieval. But to accomplish this, the information graphic must be understood and its message recognized. The paper presents our Bayesian system for recognizing the primary message of one kind of information graphic (simple bar charts) and discusses the potential role of an information graphic's message in indexing graphics and summarizing multimodal documents.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {581–588},
numpages = {8},
keywords = {graphics, multimedia, Bayesian reasoning, summarization},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148271,
author = {Otterbacher, Jahna and Radev, Dragomir and Kareem, Omer},
title = {News to Go: Hierarchical Text Summarization for Mobile Devices},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148271},
doi = {10.1145/1148170.1148271},
abstract = {We present an evaluation of a novel hierarchical text summarization method that allows users to view summaries of Web documents from small, mobile devices. Unlike previous approaches, ours does not require the documents to be in HTML since it infers a hierarchical structure automatically. Currently, the method is used to summarize news articles sent to a Web mail account in plain text format. Subjects used a Web-enabled mobile phone emulator to access the account's inbox and view the summarized news articles. They then used the summaries to complete several information-seeking tasks, which involved answering factual questions about the stories. In comparing the hierarchical text summary setting to that in which subjects were given the full text articles, there was no significant difference in task accuracy or the time taken to complete the task. However, in the hierarchical summarization setting, the number of bytes transferred per user request is less than half that of the full text case. Finally, in comparing the new method to three other summarization methods, subjects achieved significantly better accuracy on the tasks when using hierarchical summaries.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {589–596},
numpages = {8},
keywords = {mobile computing, summarization},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148273,
author = {Alonso, Omar and Gertz, Michael},
title = {Clustering of Search Results Using Temporal Attributes},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148273},
doi = {10.1145/1148170.1148273},
abstract = {Clustering of search results is an important feature in many of today's information retrieval applications. The notion of hit list clustering appears in Web search engines and enterprise search engines as a mechanism that allows users to further explore the coverage of a query. However, there has been little work on exposing temporal attributes for constructing and presentation of clusters. These attributes appear in documents as part of the textual content, e.g., as a date and time token or as a temporal reference in a sentence. In this paper, we outline a model and describe a prototype that shows the main ideas.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {597–598},
numpages = {2},
keywords = {user interfaces, clustering, experimentation, information extraction, temporal retrieval},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148274,
author = {Argamon, S. and Agam, G. and Frieder, O. and Grossman, D. and Lewis, D. and Sohn, G. and Voorhees, K.},
title = {A Complex Document Information Processing Prototype},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148274},
doi = {10.1145/1148170.1148274},
abstract = {We developed a prototype for integrated retrieval and aggregation of diverse information contained in scanned paper documents. Such complex document information processing combines several forms of image processing together with textual/linguistic processing to enable effective analysis of complex document collections, a necessity for a wide range of applications. This is the first system to attempt integrated retrieval from complex documents; we report its current capabilities.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {599–600},
numpages = {2},
keywords = {CDIP, integrated retrieval, document image processing},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148275,
author = {Aslam, Javed A. and Yilmaz, Emine},
title = {Inferring Document Relevance via Average Precision},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148275},
doi = {10.1145/1148170.1148275},
abstract = {We consider the problem of evaluating retrieval systems using a limited number of relevance judgments. Recent work has demonstrated that one can accurately estimate average precision via a judged pool corresponding to a relatively small random sample of documents. In this work, we demonstrate that given values or estimates of average precision, one can accurately infer the relevances of unjudged documents. Combined, we thus show how one can efficiently and accurately infer a large judged pool from a relatively small number of judged documents, thus permitting accurate and efficient retrieval evaluation on a large scale.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {601–602},
numpages = {2},
keywords = {average precision, relevance judgments},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148276,
author = {Azzopardi, Leif and de Rijke, Maarten},
title = {Automatic Construction of Known-Item Finding Test Beds},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148276},
doi = {10.1145/1148170.1148276},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {603–604},
numpages = {2},
keywords = {simulation, test collection formation, evaluation},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148277,
author = {Azzopardi, Leif and Baillie, Mark and Crestani, Fabio},
title = {Adaptive Query-Based Sampling for Distributed IR},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148277},
doi = {10.1145/1148170.1148277},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {605–606},
numpages = {2},
keywords = {distributed Information retrieval, selection accuracy, query-based sampling, efficiency},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148278,
author = {Baillie, Mark and Crestani, Fabio and Landoni, Monica},
title = {PENG: Integrated Search of Distributed News Archives},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148278},
doi = {10.1145/1148170.1148278},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {607–608},
numpages = {2},
keywords = {personalisation, news search},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148279,
author = {Baillie, Mark and Ruthven, Ian},
title = {Examining Assessor Attributes at HARD 2005},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148279},
doi = {10.1145/1148170.1148279},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {609–610},
numpages = {2},
keywords = {clarification forms, query expansion},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148280,
author = {Betsi, Stamatina and Lalmas, Mounia and Tombros, Anastasios and Tsikrika, Theodora},
title = {User Expectations from XML Element Retrieval},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148280},
doi = {10.1145/1148170.1148280},
abstract = {The primary aim of XML element retrieval is to return to users XML elements, rather than whole documents. This poster describes a small study, in which we elicited users' expectations, i.e. their anticipated experience, when interacting with an XML retrieval system, as compared to a traditional 'flat' document retrieval system.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {611–612},
numpages = {2},
keywords = {element retrieval, XML, user study},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148281,
author = {Blanke, Tobias and Lalmas, Mounia},
title = {Theoretical Benchmarks of XML Retrieval},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148281},
doi = {10.1145/1148170.1148281},
abstract = {This poster investigates the use of theoretical benchmarks to describe the matching functions of XML retrieval systems and the properties of specificity and exhaustivity in XML retrieval. Theoretical benchmarks concern the formal representation of qualitative properties of IR models. To this end, Situation Theory framework for the meta-evaluation of XML retrieval is presented.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {613–614},
numpages = {2},
keywords = {XML retrieval, meta-evaluation},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148282,
author = {Blunsom, Phil and Kocik, Krystle and Curran, James R.},
title = {Question Classification with Log-Linear Models},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148282},
doi = {10.1145/1148170.1148282},
abstract = {Question classification has become a crucial step in modern question answering systems. Previous work has demonstrated the effectiveness of statistical machine learning approaches to this problem. This paper presents a new approach to building a question classifier using log-linear models. Evidence from a rich and diverse set of syntactic and semantic features is evaluated, as well as approaches which exploit the hierarchical structure of the question classes.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {615–616},
numpages = {2},
keywords = {question answering, question classification, machine learning, maximum entropy},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148283,
author = {Boydell, Ois\'{\i}n and Smyth, Barry},
title = {Community-Based Snippet-Indexes for Pseudo-Anonymous Personalization in Web Search},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148283},
doi = {10.1145/1148170.1148283},
abstract = {We describe and evaluate an approach to personalizing Web search that involves post-processing the results returned by some underlying search engine so that they re .ect the interests of a community of like-minded searchers.To do this we leverage the search experiences of the community by mining the title and snippet texts of results that have been selected by community members in response to their queries. Our approach seeks to build a community-based snippet index that re .ects the evolving interests of a group of searchers. This index is then sed to re-rank the results returned by the underlying search engine by boosting the ranking of key results that have been freq ently selected for similar q eries by community members in the past.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {617–618},
numpages = {2},
keywords = {web search, personalization, community},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148284,
author = {Buckley, Chris and Dimmick, Darrin and Soboroff, Ian and Voorhees, Ellen},
title = {Bias and the Limits of Pooling},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148284},
doi = {10.1145/1148170.1148284},
abstract = {Modern retrieval test collections are built through a process called pooling in which only a sample of the entire document set is judged for each topic. The idea behind pooling is to find enough relevant documents such that when unjudged documents are assumed to be nonrelevant the resulting judgment set is sufficiently complete and unbiased. As document sets grow larger, a constant-size pool represents an increasingly small percentage of the document set, and at some point the assumption of approximately complete judgments must become invalid.This paper demonstrates that the AQUAINT 2005 test collection exhibits bias caused by pools that were too shallow for the document set size despite having many diverse runs contribute to the pools. The existing judgment set favors relevant documents that contain topic title words even though relevant documents containing few topic title words are known to exist in the document set. The paper concludes with suggested modifications to traditional pooling and evaluation methodology that may allow very large reusable test collections to be built.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {619–620},
numpages = {2},
keywords = {pooling, retrieval test collections},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148285,
author = {B\"{u}ttcher, Stefan and Clarke, Charles L. A. and Lushman, Brad},
title = {Term Proximity Scoring for Ad-Hoc Retrieval on Very Large Text Collections},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148285},
doi = {10.1145/1148170.1148285},
abstract = {We propose an integration of term proximity scoring into Okapi BM25. The relative retrieval effectiveness of our retrieval method, compared to pure BM25, varies from collection to collection.We present an experimental evaluation of our method and show that the gains achieved over BM25 as the size of the underlying text collection increases. We also show that for stemmed queries the impact of term proximity scoring is larger than for unstemmed queries.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {621–622},
numpages = {2},
keywords = {information retrieval, term proximity, query processing},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148286,
author = {Buzikashvili, Nikolai (Nick)},
title = {An Exploratory Web Log Study of Multitasking},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148286},
doi = {10.1145/1148170.1148286},
abstract = {The Web search multitasking study based on automatic task session detection procedure is described. The results of the study: 1) multitasking is very rare, 2) it usually covers only 2 task sessions, 3) it is frequently formed into a temporal inclusion of an interrupting task session into the interrupted session, 4) the quantitative characteristics of multitasking greatly differ from the characteristics of sequential execution of one and several tasks. A searcher minimizes task switching costs: he avoids multitasking and while multitasking he uses cheapest manner of task switching.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {623–624},
numpages = {2},
keywords = {multitasking, web log analysis},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148287,
author = {Cai, Deng and He, Xiaofei and Han, Jiawei},
title = {Tensor Space Model for Document Analysis},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148287},
doi = {10.1145/1148170.1148287},
abstract = {Vector Space Model (VSM) has been at the core of information retrieval for the past decades. VSM considers the documents as vectors in high dimensional space.In such a vector space, techniques like Latent Semantic Indexing (LSI), Support Vector Machines (SVM), Naive Bayes, etc., can be then applied for indexing and classification. However, in some cases, the dimensionality of the document space might be extremely large, which makes these techniques infeasible due to the curse of dimensionality. In this paper, we propose a novel Tensor Space Model for document analysis. We represent documents as the second order tensors, or matrices. Correspondingly, a novel indexing algorithm called Tensor Latent Semantic Indexing (TensorLSI) is developed in the tensor space. Our theoretical analysis shows that TensorLSI is much more computationally efficient than the conventional Latent Semantic Indexing, which makes it applicable for extremely large scale data set. Several experimental results on standard document data sets demonstrate the efficiency and effectiveness of our algorithm.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {625–626},
numpages = {2},
keywords = {tensor space model, tensor latent semantic indexing, latent semantic indexing, vector space model},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148288,
author = {Can, Fazli and Kocberber, Seyit and Balcik, Erman and Kaynak, Cihan and Ocalan, H. Cagdas and Vursavas, Onur M.},
title = {First Large-Scale Information Retrieval Experiments on Turkish Texts},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148288},
doi = {10.1145/1148170.1148288},
abstract = {We present the results of the first large-scale Turkish information retrieval experiments performed on a TREC-like test collection. The test bed, which has been created for this study, contains 95.5 million words, 408,305 documents, 72 ad hoc queries and has a size of about 800MB. All documents come from the Turkish newspaper Milliyet. We implement and apply simple to sophisticated stemmers and various query-document matching functions and show that truncating words at a prefix length of 5 creates an effective retrieval environment in Turkish. However, a lemmatizer-based stemmer provides significantly better effectiveness over a variety of matching functions.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {627–628},
numpages = {2},
keywords = {IR test collection creation, stemming, turkish, lemmatizer},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148289,
author = {Carterette, Ben and Petkova, Desislava},
title = {Learning a Ranking from Pairwise Preferences},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148289},
doi = {10.1145/1148170.1148289},
abstract = {We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document preferences. Our approach requires no training data or relevance scores, and outperforms a popular voting algorithm.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {629–630},
numpages = {2},
keywords = {data fusion, information retrieval},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148290,
author = {Chai, Joyce Y. and Baldwin, Tyler and Zhang, Chen},
title = {Automated Performance Assessment in Interactive QA},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148290},
doi = {10.1145/1148170.1148290},
abstract = {In interactive question answering (QA), users and systems take turns to ask questions and provide answers. In such an interactive setting, user questions largely depend on the answers provided by the system. One question is whether user follow-up questions can provide feedback for the system to automatically assess its performance (e.g., assess whether a correct answer is delivered). This self-awareness can make QA systems more intelligent for information seeking, for example, by adapting better strategies to cope with problematic situations. Therefore, this paper describes our initial investigation in addressing this problem. Our results indicate that interaction context can provide useful cues for automated performance assessment in interactive QA.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {631–632},
numpages = {2},
keywords = {performance assessment, user behavior, interactive question answering},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148291,
author = {Chase, Paul J. and Argamon, Shlomo},
title = {Stylistic Text Segmentation},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148291},
doi = {10.1145/1148170.1148291},
abstract = {This paper focuses on a method for the stylistic segmentation of text documents. Our technique involves mapping the change in a feature throughout a text. We use the linguistic features of conjunction and modality, through taxonomies from Systemic Functional Linguistics. This segmentation has applications in automated summarization, particularly of large documents.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {633–634},
numpages = {2},
keywords = {text segmentation, systemic functional linguistics},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148292,
author = {Chen, Ing-Xiang and Ho, Jui-Chi and Yang, Cheng-Zen},
title = {On Hierarchical Web Catalog Integration with Conceptual Relationships in Thesaurus},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148292},
doi = {10.1145/1148170.1148292},
abstract = {Web catalog integration is an interesting problem in current digital content management. Past studies have shown that using a flattened structure with auxiliary information extracted from the source catalog can improve the integration results. However, the nature of a flattened structure ignores the hierarchical relationships, and thus the performance improvement of catalog integration may be reduced. In this paper, we propose an enhanced hierarchical catalog integration (EHCI) approach with conceptual thesauri extracted from the source catalog. The results show that our enhanced hierarchical integration approach effectively boosts the accuracy of hierarchical catalog integration.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {635–636},
numpages = {2},
keywords = {hierarchical catalog integration, conceptual relationships, thesaurus},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148293,
author = {De Beer, Jan and Moens, Marie-Francine},
title = {Rpref: A Generalization of Bpref towards Graded Relevance Judgments},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148293},
doi = {10.1145/1148170.1148293},
abstract = {We present rpref ; our generalization of the bpref evaluation metric for assessing the quality of search engine results, given graded rather than binary user relevance judgments.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {637–638},
numpages = {2},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148294,
author = {Diao, Qian and Shan, Jiulong},
title = {A New Web Page Summarization Method},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148294},
doi = {10.1145/1148170.1148294},
abstract = {In this paper, we present a novel multi-webpage summarization algorithm. It adds the graph based ranking algorithm into the framework of Maximum Marginal Relevance (MMR) method, to not only capture the main topic of the web pages but also eliminate the redundancy existing in the sentences of the summary result. The experiment result indicates that the new approach has the better performance than the previous methods.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {639–640},
numpages = {2},
keywords = {multi-document summarization, graph based ranking algorithm, maximum marginal relevance},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148295,
author = {Ding, Chris and Li, Tao and Peng, Wei},
title = {NMF and PLSI: Equivalence and a Hybrid Algorithm},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148295},
doi = {10.1145/1148170.1148295},
abstract = {In this paper, we show that PLSI and NMF optimize the same objective function, although PLSI and NMF are different algorithms as verified by experiments. In addition, we also propose a new hybrid method that runs PLSI and NMF alternatively to achieve better solutions.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {641–642},
numpages = {2},
keywords = {chi-square, NMF, equivalence, PLSI},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148296,
author = {Fern\'{a}ndez, Miriam and Vallet, David and Castells, Pablo},
title = {Using Historical Data to Enhance Rank Aggregation},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148296},
doi = {10.1145/1148170.1148296},
abstract = {Rank aggregation is a pervading operation in IR technology. We hypothesize that the performance of score-based aggregation may be affected by artificial, usually meaningless deviations consistently occurring in the input score distributions, which distort the combined result when the individual biases differ from each other. We propose a score-based rank aggregation model where the source scores are normalized to a common distribution before being combined. Early experiments on available data from several TREC collections are shown to support our proposal.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {643–644},
numpages = {2},
keywords = {rank aggregation, score normalization, score distribution},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148297,
author = {Freund, Luanne and Toms, Elaine G.},
title = {Enterprise Search Behaviour of Software Engineers},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148297},
doi = {10.1145/1148170.1148297},
abstract = {Technical professionals spend ~25% of their time at work searching for information, and have specialized information needs that are not well-served by generic enterprise search tools. In this study, we investigated how a group of software engineers use a workplace search system. We identify patterns of search behaviour specific to this group and distinct from general web and intranet search patterns, and make design recommendations for search systems that will better serve the needs of this group.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {645–646},
numpages = {2},
keywords = {queries, search behaviour, software engineers, enterprise search},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148298,
author = {Fu, Xin and Kelly, Diane},
title = {Evaluating Sources of Query Expansion Terms},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148298},
doi = {10.1145/1148170.1148298},
abstract = {This study investigates the effectiveness of retrieval systems and human users in generating terms for query expansion. We compare three sources of terms: system generated terms, terms users select from top-ranked sentences, and user generated terms. Results demonstrate that overall the system generated more effective expansion terms than users, but that users' selection of terms improved precision at the top of the retrieved document list.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {647–648},
numpages = {2},
keywords = {query expansion, query length, source of query term},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148299,
author = {He, Daqing and Peng, Yefei},
title = {Comparing Two Blind Relevance Feedback Techniques},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148299},
doi = {10.1145/1148170.1148299},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {649–650},
numpages = {2},
keywords = {automatic query expansion, comparison, blind relevance feedback},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148300,
author = {Hsu, Ming-Hung and Chen, Hsin-Hsi},
title = {Information Retrieval with Commonsense Knowledge},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148300},
doi = {10.1145/1148170.1148300},
abstract = {This paper employs ConceptNet, which covers a rich set of commonsense concepts, to retrieve images with text descriptions by focusing on spatial relationships. Evaluation on test data of the 2005 ImageCLEF shows that integrating commonsense knowledge in information retrieval is feasible.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {651–652},
numpages = {2},
keywords = {concept expansion, ConceptNet, commonsense knowledge},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148301,
author = {Huang, Ruizhang and Zhang, Zhigang and Lam, Wai},
title = {Refining Hierarchical Taxonomy Structure via Semi-Supervised Learning},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148301},
doi = {10.1145/1148170.1148301},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {653–654},
numpages = {2},
keywords = {semi-supervised learning, metric learning},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148302,
author = {Jin, Xiangyu and French, James and Michel, Jonathan},
title = {Quantative Analysis of the Impact of Judging Inconsistency on the Performance of Relevance Feedback},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148302},
doi = {10.1145/1148170.1148302},
abstract = {Practical constrains of user interfaces make the user's judgment (during the feedback loop) deviate from real thoughts (when the full document is read).This is often overlooked in evaluation of relevance feedback.This paper quantitatively analyze the impact of judging inconsistency on the performance of relevance feedback.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {655–656},
numpages = {2},
keywords = {relevance feedback, judging inconsistency, performance evaluation},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148303,
author = {Jordan, Chris and Healy, John and Keselj, Vlado},
title = {Swordfish: An Unsupervised Ngram Based Approach to Morphological Analysis},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148303},
doi = {10.1145/1148170.1148303},
abstract = {Extracting morphemes from words is a nontrivial task. Rule based stemming approaches such as Porter's algorithm have encountered some success, however they are restricted by their ability to identify a limited number of affixes and are language dependent. When dealing with languages with many affixes, rule based approaches generally require many more rules to deal with all the possible word forms. Deriving these rules requires a larger effort on the part of linguists and in some instances can be simply impractical. We propose an unsupervised ngram based approach, named Swordfish. Using ngram probabilities in the corpus, possible morphemes are identified. We look at two possible methods for identifying candidate morphemes, one using joint probabilities between two ngrams, and the second based on log odds between prefix probabilities. Initial results indicate the joint probability approach to be better for English while the prefix ratio approach is better for Finnish and Turkish.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {657–658},
numpages = {2},
keywords = {Ngrams, morphemes},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148304,
author = {Koppel, Moshe and Schler, Jonathan and Argamon, Shlomo and Messeri, Eran},
title = {Authorship Attribution with Thousands of Candidate Authors},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148304},
doi = {10.1145/1148170.1148304},
abstract = {In this paper, we use a blog corpus to demonstrate that we can often identify the author of an anonymous text even where there are many thousands of candidate authors. Our approach combines standard information retrieval methods with a text categorization meta-learning scheme that determines when to even venture a guess.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {659–660},
numpages = {2},
keywords = {authorship attribution, blog analysis},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148305,
author = {Kumaran, Giridhar and Allan, James},
title = {Simple Questions to Improve Pseudo-Relevance Feedback Results},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148305},
doi = {10.1145/1148170.1148305},
abstract = {We explore interactive methods to further improve the performance of pseudo-relevance feedback. Studies citeria suggest that new methods for tackling difficult queries are required. Our approach is to gather more information about the query from the user by asking her simple questions. The equally simple responses are used to modify the original query. Our experiments using the TREC Robust Track queries show that we can obtain a significant improvement in mean average precision averaging around 5% over pseudo-relevance feedback. This improvement is also spread across more queries compared to ordinary pseudo-relevance feedback, as suggested by geometric mean average precision.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {661–662},
numpages = {2},
keywords = {information retrieval, feedback, user interaction},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148306,
author = {Larsen, Birger and Tombros, Anastasios and Malik, Saadia},
title = {Is XML Retrieval Meaningful to Users? Searcher Preferences for Full Documents vs. Elements},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148306},
doi = {10.1145/1148170.1148306},
abstract = {The aim of this study is to investigate whether element retrieval (as opposed to full-text retrieval) is meaningful and useful for searchers when carrying out information-seeking tasks. Our results suggest that searchers find the structural breakdown of documents useful when browsing within retrieved documents, and provide support for the usefulness of element retrieval in interactive settings.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {663–664},
numpages = {2},
keywords = {element retrieval, XML retrieval, INEX, interactive studies},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148307,
author = {Lewis, D. and Agam, G. and Argamon, S. and Frieder, O. and Grossman, D. and Heard, J.},
title = {Building a Test Collection for Complex Document Information Processing},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148307},
doi = {10.1145/1148170.1148307},
abstract = {Research and development of information access technology for scanned paper documents has been hampered by the lack of public test collections of realistic scope and complexity. As part of a project to create a prototype system for search and mining of masses of document images, we are assembling a 1.5 terabyte dataset to support evaluation of both end-to-end complex document information processing (CDIP) tasks (e.g., text retrieval and data mining) as well as component technologies such as optical character recognition (OCR), document structure analysis, signature matching, and authorship attribution.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {665–666},
numpages = {2},
keywords = {relevance judgments, queries, metadata, TREC, corpora},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148308,
author = {Li, Baoli and Li, Wenjie and Lu, Qin},
title = {Enhancing Topic Tracking with Temporal Information},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148308},
doi = {10.1145/1148170.1148308},
abstract = {In this paper, we propose a new strategy with time granularity reasoning for utilizing temporal information in topic tracking. Compared with previous ones, our work has four distinguished characteristics. Firstly, we try to determine a set of topic times for a target topic from the given on-topic stories. It helps to avoid the negative influence from other irrelevant times. Secondly, we take into account time granularity variance when deciding whether a coreference relationship exists between two times. Thirdly, both publication time and times presented in texts are considered. Finally, as time is only one attribute of a topic, we increase the similarity between a story and a target topic only when they are related not only temporally but also semantically. Experiments on two TDT corpora show that our method makes good use of temporal information in news stories.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {667–668},
numpages = {2},
keywords = {topic tracking, temporal information processing},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148309,
author = {Li, Yuelin and Zhang, Xiangmin and Zhang, Ying and Liu, Jingjing},
title = {A Comparative Study of the Effect of Search Feature Design on User Experience in Digital Libraries (DLs)},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148309},
doi = {10.1145/1148170.1148309},
abstract = {This study investigates the impact of different search feature designs in DLs on user search experience. The results indicate that the impact is significant in terms of the number of queries issued, search steps, zero-hits pages returned, and search errors.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {669–670},
numpages = {2},
keywords = {digital libraries, user search experience, search feature design},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148310,
author = {Liu, Xiaoyong and Croft, W. Bruce},
title = {Representing Clusters for Retrieval},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148310},
doi = {10.1145/1148170.1148310},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {671–672},
numpages = {2},
keywords = {cluster-based retrieval, cluster representation},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148311,
author = {Liu, Baolong and Oard, Douglas W.},
title = {One-Sided Measures for Evaluating Ranked Retrieval Effectiveness with Spontaneous Conversational Speech},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148311},
doi = {10.1145/1148170.1148311},
abstract = {Early speech retrieval experiments focused on news broadcasts, for which adequate Automatic Speech Recognition (ASR) accuracy could be obtained. Like newspapers, news broadcasts are a manually selected and arranged set of stories. Evaluation designs reflected that, using known story boundaries as a basis for evaluation. Substantial advances in ASR accuracy now make it possible to build search systems for some types of spontaneous conversational speech, but present evaluation designs continue to rely on known topic boundaries that are no longer well matched to the nature of the materials. We propose a new class of measures for speech retrieval based on manual annotation of points at which a user with specific topical interests would wish replay to begin.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {673–674},
numpages = {2},
keywords = {speech retrieval, evaluation measures, simulation},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148312,
author = {Macdonald, Craig and Ounis, Iadh},
title = {Combining Fields in Known-Item Email Search},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148312},
doi = {10.1145/1148170.1148312},
abstract = {Emails are examples of structured documents with various fields. These fields can be exploited to enhance the retrieval effectiveness of an Information Retrieval (IR) system that mailing list archives. In recent experiments of the TREC2005 Enterprise track, various fields were applied to varying degrees of success by the participants. In his work, using a field-based weighting model, we investigate the retrieval performance attainable by each field, and examine when fields evidence should be combined or not.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {675–676},
numpages = {2},
keywords = {retrieval, email, metadata, structure, fields},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148313,
author = {Mayfield, James and McNamee, Paul},
title = {Improving QA Retrieval Using Document Priors},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148313},
doi = {10.1145/1148170.1148313},
abstract = {We present a simple way to improve document retrieval for question answering systems. The method biases the retrieval system toward documents that contain words that have appeared in other documents containing answers to the same type of question. The method works with virtually any retrieval system, and exhibits a statistically significant performance improvement over a strong baseline.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {677–678},
numpages = {2},
keywords = {document retrieval, question answering, document priors},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148314,
author = {Mu, Xiangming},
title = {Content-Based Video Retrieval: Does Video's Semantic Visual Feature Matter?},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148314},
doi = {10.1145/1148170.1148314},
abstract = {A new shot level video browsing method based on semantic visual features (e.g., car, mountain, and fire) is proposed to facilitate content-based retrieval. The video's binary semantic feature vector is utilized to calculate the score of similarity between two shot keyframes. The score is then used to browse the "similar" keyframes in terms of semantic visual features. A pilot user study was conducted to better understand users' behaviors in video retrieval context. Three video retrieval and browsing systems are compared: temporal neighbor, semantic visual feature, and fused browsing system. The initial results indicated that the semantic visual feature browsing was effective and efficient for Visual Centric tasks, but not for Non-visual Centric tasks.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {679–680},
numpages = {2},
keywords = {content-based, user interface, video browsing, video retrieval},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148315,
author = {Murray, G. Craig and Lin, Jimmy and Chowdhury, Abdur},
title = {Action Modeling: Language Models That Predict Query Behavior},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148315},
doi = {10.1145/1148170.1148315},
abstract = {We present a novel language modeling approach to capturing the query reformulation behavior of Web search users. Based on a framework that categorizes eight different types of "user moves" (adding/removing query terms, etc.), we treat search sessions as sequence data and build n-gram language models to capture user behavior. We evaluated our models in a prediction task. The results suggest that useful patterns of activity can be extracted from user histories. Furthermore, by examining prediction performance under different order n-gram models, we gained insight into the amount of history/context that is associated with different types of user actions. Our work serves as the basis for more refined user models.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {681–682},
numpages = {2},
keywords = {web search, query reformulation, query modeling, user models},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148316,
author = {Nagura, Ryosuke and Seki, Yohei and Kando, Noriko and Aono, Masaki},
title = {A Method of Rating the Credibility of News Documents on the Web},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148316},
doi = {10.1145/1148170.1148316},
abstract = {We propose a method to rate the credibility of news articles using three clues: (1) commonality of the contents of articles among different news publishers; (2) numerical agreement versus contradiction of numerical values reported in the articles; and (3) objectivity based on subjective speculative phrases and news sources. We tested this method on news stories taken from seven different news sites on the Web. The average agreement between the system-produced "credibility" and the manual judgments of three human assessors on the 52 sample articles was 69.1%. The limitations of the current approach and future directions are discussed.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {683–684},
numpages = {2},
keywords = {information filtering, web document credibility},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148317,
author = {Olsson, J. Scott},
title = {An Analysis of the Coupling between Training Set and Neighborhood Sizes for the <i>k</i>NN Classifier},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148317},
doi = {10.1145/1148170.1148317},
abstract = {We consider the relationship between training set size and the parameter k for the k-Nearest Neighbors (kNN) classifier. When few examples are available, we observe that accuracy is sensitive to k and that best k tends to increase with training size. We explore the subsequent risk that k tuned on partitions will be suboptimal after aggregation and re-training. This risk is found to be most severe when little data is available. For larger training sizes, accuracy becomes increasingly stable with respect to k and the risk decreases.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {685–686},
numpages = {2},
keywords = {k-Nearest Neighbors, parameter stability, parameter tuning, text classification},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148318,
author = {Otterbacher, Jahna and Radev, Dragomir},
title = {Fact-Focused Novelty Detection: A Feasibility Study},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148318},
doi = {10.1145/1148170.1148318},
abstract = {Methods for detecting sentences in an input document set, which are both relevant and novel with respect to an information need, would be of direct benefit to many systems, such as extractive text summarizers. However, satisfactory levels of agreement between judges performing this task manually have yet to demonstrated, leaving researchers to conclude that the task is too subjective. In previous experiments, judges were asked to first identify sentences that are relevant to a general topic, and then to eliminate sentences from the list that do not contain new information. Currently, a new task is proposed, in which annotators perform the same procedure, but within the context of a specific, factual information need. In the experiment, satisfactory levels of agreement between independent annotators were achieved on the first step of identifying sentences containing relevant information relevant. However, the results indicate that judges do not agree on which sentences contain novel information.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {687–688},
numpages = {2},
keywords = {summarization, novelty},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148319,
author = {Parikh, Jignashu and Kapur, Shyam},
title = {Unity: Relevance Feedback Using User Query Logs},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148319},
doi = {10.1145/1148170.1148319},
abstract = {The exponential growth of the Web and the increasing ability of web search engines to index data have led to a problem of plenty. The number of results returned per query is typically in the order of millions of documents for many common queries. Although there is the benefit of added coverage for every query, the problem of ranking these documents and giving the best results gets worse. The problem is even more difficult in case of temporal and ambiguous queries. We try to address this problem using feedback from user query logs. We leverage a technology called Units for generating query refinements which are shown as Also try queries on Yahoo! Search. We consider these refinements as sub-concepts which help define user intent and use them to improve search relevance. The results obtained via live testing on Yahoo! Search are encouraging.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {689–690},
numpages = {2},
keywords = {search engines, search re-ranking, relevance feedback, information retrieval, query expansion, query refinements},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148320,
author = {Radlinski, Filip and Dumais, Susan},
title = {Improving Personalized Web Search Using Result Diversification},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148320},
doi = {10.1145/1148170.1148320},
abstract = {We present and evaluate methods for diversifying search results to improve personalized web search. A common personalization approach involves reranking the top N search results such that documents likely to be preferred by the user are presented higher. The usefulness of reranking is limited in part by the number and diversity of results considered. We propose three methods to increase the diversity of the top results and evaluate the effectiveness of these methods.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {691–692},
numpages = {2},
keywords = {result diversity, personalized web search},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148321,
author = {Ramirez, Georgina and Westerveld, Thijs and de Vries, Arjen P.},
title = {Using Small XML Elements to Support Relevance},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148321},
doi = {10.1145/1148170.1148321},
abstract = {Small XML elements are often estimated relevant by the retrieval model but they are not desirable retrieval units. This paper presents a generic model that exploits the information obtained from small elements. We identify relationships between small and relevant elements and use this linking information to reinforce the relevance of other elements before removing the small ones. Our experiments using the INEX testbed show the effectiveness of our approach.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {693–694},
numpages = {2},
keywords = {score propagation, length normalization, XML retrieval},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148322,
author = {Sakai, Tetsuya},
title = {Give Me Just One Highly Relevant Document: P-Measure},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148322},
doi = {10.1145/1148170.1148322},
abstract = {We introduce an evaluation metric called P-measure for the task of retrieving one highly relevant document. It models user behaviour in practical tasks such as known-item search, and is more stable and sensitive than Reciprocal Rank which cannot handle graded relevance.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {695–696},
numpages = {2},
keywords = {evaluation metrics, test collection},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148323,
author = {Sevillano, Xavier and Cobo, Germ\'{a}n and Al\'{\i}as, Francesc and Socor\'{o}, Joan Claudi},
title = {Feature Diversity in Cluster Ensembles for Robust Document Clustering},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148323},
doi = {10.1145/1148170.1148323},
abstract = {The performance of document clustering systems depends on employing optimal text representations, which are not only difficult to determine beforehand, but also may vary from one clustering problem to another. As a first step towards building robust document clusterers, a strategy based on feature diversity and cluster ensembles is presented in this work. Experiments conducted on a binary clustering problem show that our method is robust to near-optimal model order selection and able to detect constructive interactions between different document representations in the test bed.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {697–698},
numpages = {2},
keywords = {cluster ensembles, document clustering, feature extraction},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148324,
author = {Smucker, Mark D. and Allan, James},
title = {Lightening the Load of Document Smoothing for Better Language Modeling Retrieval},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148324},
doi = {10.1145/1148170.1148324},
abstract = {We hypothesized that language modeling retrieval would improve if we reduced the need for document smoothing to provide an inverse document frequency (IDF) like effect. We created inverse collection frequency (ICF) weighted query models as a tool to partially separate the IDF-like role from document smoothing. Compared to maximum likelihood estimated (MLE) queries, the ICF weighted queries achieved a 6.4% improvement in mean average precision on description queries. The ICF weighted queries performed better with less document smoothing than that required by MLE queries. Language modeling retrieval may benefit from a means to separately incorporate an IDF-like behavior outside of document smoothing.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {699–700},
numpages = {2},
keywords = {IDF, inverse document frequency, document smoothing, language modeling},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148325,
author = {Stein, Sterling Stuart and Argamon, Shlomo and Frieder, Ophir},
title = {The Effect of OCR Errors on Stylistic Text Classification},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148325},
doi = {10.1145/1148170.1148325},
abstract = {Recently, interest is growing in non-topical text classification tasks such as genre classification, sentiment analysis, and authorship profiling. We study to what extent OCR errors affect stylistic text classification from scanned documents. We find that even a relatively high level of errors in the OCRed documents does not substantially affect stylistic classification accuracy.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {701–702},
numpages = {2},
keywords = {text classification, OCR errors, OCR},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148326,
author = {Teevan, Jaime and Adar, Eytan and Jones, Rosie and Potts, Michael},
title = {History Repeats Itself: Repeat Queries in Yahoo's Logs},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148326},
doi = {10.1145/1148170.1148326},
abstract = {Thanks to the ubiquity of the Internet search engine search box, users have come to depend on search engines both to find and re-find information. However, re-finding behavior has not been significantly addressed. Here we look at re-finding queries issued to the Yahoo! search engine by 114 users over a year.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {703–704},
numpages = {2},
keywords = {web search, repeat queries, query log analysis, re-finding},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148327,
author = {Tomlinson, Stephen},
title = {Early Precision Measures: Implications from the Downside of Blind Feedback},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148327},
doi = {10.1145/1148170.1148327},
abstract = {We report the statistically significant mean impacts of blind feedback, as implemented by 7 participants for the 2003 Reliable Information Access (RIA) Workshop, on 30 retrieval measures, including several primary recall measures not originally reported. We find that blind feedback was detrimental to measures focused on the first relevant item even when it boosted "early precision" measures such as mean Precision@10, implying that the conventional reporting of ad hoc precision needs enhancement.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {705–706},
numpages = {2},
keywords = {robust retrieval, early precision, blind feedback},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148328,
author = {Treeratpituk, Pucktada and Callan, Jamie},
title = {An Experimental Study on Automatically Labeling Hierarchical Clusters Using Statistical Features},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148328},
doi = {10.1145/1148170.1148328},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {707–708},
numpages = {2},
keywords = {cluster labeling, document hierarchy},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148329,
author = {Trotman, Andrew and Lalmas, Mounia},
title = {Strict and Vague Interpretation of XML-Retrieval Queries},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148329},
doi = {10.1145/1148170.1148329},
abstract = {Structural hints in XML-retrieval queries can be used to specify both the granularity of the search result (the target element) and where in a document to search (support elements). These hints might be interpreted either strictly or vaguely, but does it matter if an XML search engine interprets these in one way and the user in another? The performance of all runs submitted to INEX 2005 content and structure (CAS) tasks were measured for each of four different interpretations of CAS. Runs that perform well for one interpretation of target elements do so regardless of the interpretation of support elements; but how to interpret the target element does matter. This suggests that to perform well on all CAS queries it is necessary to know how the target structure specification should be interpreted. We extend the NEXI query language to include this, and hypothesize that using this will increase the overall performance of search engines.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {709–710},
numpages = {2},
keywords = {XML retrieval, INEX, element retrieval},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148330,
author = {Trotman, Andrew and Lalmas, Mounia},
title = {Why Structural Hints in Queries Do Not Help XML-Retrieval},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148330},
doi = {10.1145/1148170.1148330},
abstract = {For many years it has been commonly held that a user who adds structural "hints" to a query will improve precision in an element retrieval search. At INEX 2005 we conducted an experiment to test this assumption. We present the unexpected result that structural hints in queries do not improve precision. An analysis of the topics and the judgments suggests that this is because users are particularly bad at giving structural hints.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {711–712},
numpages = {2},
keywords = {element retrieval, INEX, XML retrieval},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148331,
author = {Varadarajan, Ramakrishna and Hristidis, Vagelis and Li, Tao},
title = {Searching the Web Using Composed Pages},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148331},
doi = {10.1145/1148170.1148331},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {713–714},
numpages = {2},
keywords = {composed pages},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148332,
author = {White, Ryen W. and Marchionini, Gary},
title = {A Study of Real-Time Query Expansion Effectiveness},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148332},
doi = {10.1145/1148170.1148332},
abstract = {In this poster, we describe the study of an interface technique that provides a list of suggested additional query terms as a searcher types a search query, in effect offering interactive query expansion (IQE) options while the query is formulated. Analysis of the results shows that offering IQE during query formulation leads to better quality initial queries, and an increased uptake of query expansion. These findings have implications for how IQE should be offered in retrieval interfaces.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {715–716},
numpages = {2},
keywords = {query quality, real-time query expansion},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148333,
author = {Wu, Ming and Jin, Rong},
title = {A Graph-Based Framework for Relation Propagation and Its Application to Multi-Label Learning},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148333},
doi = {10.1145/1148170.1148333},
abstract = {Label propagation exploits the structure of the unlabeled documents by propagating the label information of the training documents to the unlabeled documents. The limitation with the existing label propagation approaches is that they can only deal with a single type of objects. We propose a framework, named "relation propagation", that allows for information propagated among multiple types of objects. Empirical studies with multi-label text categorization showed that the proposed algorithm is more effective than several semi-supervised learning algorithms in that it is capable of exploring the correlation among different categories and the structure of unlabeled documents simultaneously.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {717–718},
numpages = {2},
keywords = {label propagation, relation propagation, semi-supervised learning, graph laplacian},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148334,
author = {Yang, Christopher C. and Liu, Nan},
title = {Measuring Similarity of Semi-Structured Documents with Context Weights},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148334},
doi = {10.1145/1148170.1148334},
abstract = {In this work, we study similarity measures for text-centric XML documents based on an extended vector space model, which considers both document content and structure. Experimental results based on a benchmark showed superior performance of the proposed measure over the baseline which ignores structural knowledge of XML documents.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {719–720},
numpages = {2},
keywords = {models, XML search and retrieval},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148335,
author = {Zha, Hongyuan and Zheng, Zhaohui and Fu, Haoying and Sun, Gordon},
title = {Incorporating Query Difference for Learning Retrieval Functions in Information Retrieval},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148335},
doi = {10.1145/1148170.1148335},
abstract = {We discuss information retrieval methods that aim at serving a diverse stream of user queries. We propose methods that emphasize the importance of taking into consideration of query difference in learning effective retrieval functions. We formulate the problem as a multi-task learning problem using a risk minimization framework. In particular, we show how to calibrate the empirical risk to incorporate query difference in terms of introducing nuisance parameters in the statistical models, and we also propose an alternating optimization method to simultaneously learn the retrieval function and the nuisance parameters. We illustrate the effectiveness of the proposed methods using modeling data extracted from a commercial search engine.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {721–722},
numpages = {2},
keywords = {retrieval function, query document features, query dependence, relevance, machine learning, regularization, least-squares regression},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148336,
author = {Zhong, Ming and Huang, Xiangji},
title = {Concept-Based Biomedical Text Retrieval},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148336},
doi = {10.1145/1148170.1148336},
abstract = {One challenging problem for biomedical text retrieval is to find accurate synonyms or name variants for biomedical entities. In this paper, we propose a new concept-based approach to tackle this problem. In this approach, a set of concepts instead of keywords will be extracted from a query first. Then these concepts will be used for retrieval purpose. The experiment results show that the proposed approach can boost the retrieval performance and it generates very good results on 2005 TREC Genomics data sets.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {723–724},
numpages = {2},
keywords = {information retrieval, biomedical text retrieval, concept},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148338,
author = {Blok, Henk Ernst and Mihajlovi\'{c}, Vojkan and Ram\'{\i}rez, Georgina and Westerveld, Thijs and Hiemstra, Djoerd and de Vries, Arjen P.},
title = {The TIJAH XML Information Retrieval System},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148338},
doi = {10.1145/1148170.1148338},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {725},
numpages = {1},
keywords = {databases, region algebra, XML, information retrieval, structured documents},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148339,
author = {Chen, Chufeng and Oakes, Michael and Tait, John},
title = {A Location Annotation System for Personal Photos},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148339},
doi = {10.1145/1148170.1148339},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {726},
numpages = {1},
keywords = {browsing, clustering, annotation},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148340,
author = {Garg, Navendu and Bloom, Kenneth and Argamon, Shlomo},
title = {Appraisal Navigator},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148340},
doi = {10.1145/1148170.1148340},
abstract = {Much interesting text n the web consists largely of opinionated or evaluative text, as opposed to directly informative text. The new field of 'sentiment analysis' seeks to characterize such aspects of natural language text, as opposed to just the bare facts. We suggest that 'appraisal expression extraction' should be viewed as a fundamental task for sentiment analysis. We define an 'appraisal expression' to be a piece of text expressing some evaluative stance towards a particular object. The task is to find these elements and characterize the type and orientation (positive or negative) of the evaluative stance, as well as its target and possibly its source. Potential applications of these methods include new approaches to the now-traditional tasks of sentiment classification and pinion mining, as well as possibly for adversarial textual analysis and intention detection for intelligence applications.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {727},
numpages = {1},
keywords = {appraisal theory, shallow parsing, sentiment analysis, appraisal extraction, opinion mining},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148341,
author = {Huang, Xiangji and Wen, Miao and An, Aijun and Huang, Yan-Rui},
title = {A Platform for Okapi-Based Contextual Information Retrieval},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148341},
doi = {10.1145/1148170.1148341},
abstract = {We present an extensible java-based platform for contextual retrieval based on the probabilistic information retrieval model. Modules for dual indexes, relevance feedback with blind or machine learning approaches and query expansion with context are integrated into the Okapi system to deal with the contextual information. This platform allows easy extension to include other types of contextual information.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {728},
numpages = {1},
keywords = {contextual information retrieval, probabilistic model},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148342,
author = {Jones, William and Bruce, Harry and Foxley, Austin},
title = {Project Contexts to Situate Personal Information},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148342},
doi = {10.1145/1148170.1148342},
abstract = {The Personal Project Planner prototype works as an extension to the file manager to provide people with rich-text overlays to their information (folders, files and also email, web pages, notes). Rich-text, document-like project plans can be created which then provide a context in which to create or reference the email messages, electronic documents, web pages, etc. that are needed to complete the plan. The user can later locate an information item such as an email message with reference to the plan (e.g., as an alternative to a mostly context-free search through the inbox or sent mail). The Planner explores a possibility that an effective organization of project-related information can emerge as a natural by-product of efforts to plan and structure the project.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {729},
numpages = {1},
keywords = {contextualized search, re-finding & re-use of personal information, personal project planning, personal information management},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148343,
author = {Larson, Ray R. and Sanderson, Robert},
title = {Cheshire3: Retrieving from Tera-Scale Grid-Based Digital Libraries},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148343},
doi = {10.1145/1148170.1148343},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {730},
numpages = {1},
keywords = {grid-based digital libraries},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148344,
author = {Li, Haobin and Rafiei, Davood},
title = {DeWild: A Tool for Searching the Web Using Wild Cards},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148344},
doi = {10.1145/1148170.1148344},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {731},
numpages = {1},
keywords = {web search, DeWild, data extraction},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148345,
author = {Macdonald, Craig and Ounis, Iadh},
title = {Searching for Expertise Using the Terrier Platform},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148345},
doi = {10.1145/1148170.1148345},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {732},
numpages = {1},
keywords = {expert search information retrieval, expert finding, terrier, expertise modelling},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148346,
author = {Mao, Ming and Peng, Yefei and He, Daqing},
title = {DiLight: An Ontology-Based Information Access System for e-Learning Environments},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148346},
doi = {10.1145/1148170.1148346},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {733},
numpages = {1},
keywords = {DiLight, ontology, e-Learn, information access},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148347,
author = {Mu, Xiangming},
title = {Supporting Semantic Visual Feature Browsing in Contentbased Video Retrieval},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148347},
doi = {10.1145/1148170.1148347},
abstract = {A new shot level video retrieval system that supports semantic visual features (e.g., car, mountain, and fire) browsing is developed to facilitate content-based retrieval. The video's binary semantic feature vector is utilized to calculate the score of similarity between two shot keyframes. The score is then used to browse the "similar" keyframes in terms of semantic visual features.},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {734},
numpages = {1},
keywords = {content-based, user interface, video browsing, video retrieval},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

@inproceedings{10.1145/1148170.1148348,
author = {Munavalli, Rajesh and Miner, Robert},
title = {MathFind: A Math-Aware Search Engine},
year = {2006},
isbn = {1595933697},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1148170.1148348},
doi = {10.1145/1148170.1148348},
booktitle = {Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {735},
numpages = {1},
keywords = {MathML, math search, equation editor},
location = {Seattle, Washington, USA},
series = {SIGIR '06}
}

license_type: permissive

extension: bib


text:
@article{Adabag2008a,
 author = {Adabag, A.S. and Maron, B.J. and Appelbaum, E. and Harrigan, C.J. and Buros, J.L. and Gibson, C.M. and Lesser, J.R. and Hanna, C.A. and Udelson, J.E. and Manning, W.J. and Maron, M.S.},
 doi = {10.1016/j.jacc.2008.06.017},
 issn = {07351097},
 journal = {Journal of the American College of Cardiology},
 number = {11},
 title = {Reply},
 volume = {52},
 year = {2008}
}

license: MIT

repository: jburos/another-biostats-blog

repo_name: jburos/another-biostats-blog

branch_name: refs/heads/master

gha_license_id: MIT

gha_language: TeX


text:
SECTION = "devel/chicken"
DESCRIPTION = "A tool to generate manifests for Ugarit archival mode"
LICENSE = "BSD"
LIC_FILES_CHKSUM = "file://ugarit-manifest-maker.meta;md5=0517fad2e2e810ae32507eae32f7211d"
DEPENDS_append_class-cross = " chicken-egg-matchable-cross chicken-egg-srfi-37-cross chicken-egg-fnmatch-cross chicken-egg-miscmacros-cross chicken-egg-ugarit-cross chicken-egg-numbers-cross"
DEPENDS_append_class-crosssdk = " chicken-egg-matchable-crosssdk chicken-egg-srfi-37-crosssdk chicken-egg-fnmatch-crosssdk chicken-egg-miscmacros-crosssdk chicken-egg-ugarit-crosssdk chicken-egg-numbers-crosssdk"
DEPENDS_append_class-nativesdk = " nativesdk-chicken-egg-matchable nativesdk-chicken-egg-srfi-37 nativesdk-chicken-egg-fnmatch nativesdk-chicken-egg-miscmacros nativesdk-chicken-egg-ugarit nativesdk-chicken-egg-numbers chicken-egg-matchable-crosssdk chicken-egg-srfi-37-crosssdk chicken-egg-fnmatch-crosssdk chicken-egg-miscmacros-crosssdk chicken-egg-ugarit-crosssdk chicken-egg-numbers-crosssdk"
DEPENDS = " chicken-egg-matchable chicken-egg-srfi-37 chicken-egg-fnmatch chicken-egg-miscmacros chicken-egg-ugarit chicken-egg-numbers chicken-egg-matchable-cross chicken-egg-srfi-37-cross chicken-egg-fnmatch-cross chicken-egg-miscmacros-cross chicken-egg-ugarit-cross chicken-egg-numbers-cross"
RDEPENDS_${PN} = " chicken-egg-matchable chicken-egg-srfi-37 chicken-egg-fnmatch chicken-egg-miscmacros chicken-egg-ugarit chicken-egg-numbers"

SRC_URI = "http://code.call-cc.org/egg-tarballs/4/ugarit-manifest-maker/ugarit-manifest-maker-${PV}.tar.gz"

SRC_URI[md5sum] = "5ce749a491297f3c5100ff4fdaf8a97d"
SRC_URI[sha256sum] = "62da52d20c9cb8dd4e82956a48a106ab6a4f45250b2b812503bc783cf4e85140"

S = "${WORKDIR}/ugarit-manifest-maker-${PV}"

inherit chicken_install

BBCLASSEXTEND = "cross crosssdk nativesdk"

repository: OSSystems/meta-chicken

repo_name: OSSystems/meta-chicken

extension: bb


text:
@proceedings{emnlp-2019-new,
    title = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    editor = "Wang, Lu  and
      Cheung, Jackie Chi Kit  and
      Carenini, Giuseppe  and
      Liu, Fei",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5400",
}
@inproceedings{pal-etal-2019-answering,
    title = "Answering Naturally: Factoid to Full length Answer Generation",
    author = "Pal, Vaishali  and
      Shrivastava, Manish  and
      Bhat, Irshad",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5401",
    doi = "10.18653/v1/D19-5401",
    pages = "1--9",
}
@inproceedings{bae-etal-2019-summary,
    title = "Summary Level Training of Sentence Rewriting for Abstractive Summarization",
    author = "Bae, Sanghwan  and
      Kim, Taeuk  and
      Kim, Jihoon  and
      Lee, Sang-goo",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5402",
    doi = "10.18653/v1/D19-5402",
    pages = "10--20",
}
@inproceedings{steen-markert-2019-abstractive,
    title = "Abstractive Timeline Summarization",
    author = "Steen, Julius  and
      Markert, Katja",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5403",
    doi = "10.18653/v1/D19-5403",
    pages = "21--31",
}
@inproceedings{antognini-faltings-2019-learning,
    title = "Learning to Create Sentence Semantic Relation Graphs for Multi-Document Summarization",
    author = "Antognini, Diego  and
      Faltings, Boi",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5404",
    doi = "10.18653/v1/D19-5404",
    pages = "32--41",
}
@inproceedings{coavoux-etal-2019-unsupervised,
    title = "Unsupervised Aspect-Based Multi-Document Abstractive Summarization",
    author = "Coavoux, Maximin  and
      Elsahar, Hady  and
      Gall{\'e}, Matthias",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5405",
    doi = "10.18653/v1/D19-5405",
    pages = "42--47",
}
@inproceedings{kornilova-eidelman-2019-billsum,
    title = "{B}ill{S}um: A Corpus for Automatic Summarization of {US} Legislation",
    author = "Kornilova, Anastassia  and
      Eidelman, Vladimir",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5406",
    doi = "10.18653/v1/D19-5406",
    pages = "48--56",
}
@inproceedings{moroshko-etal-2019-editorial,
    title = "An Editorial Network for Enhanced Document Summarization",
    author = "Moroshko, Edward  and
      Feigenblat, Guy  and
      Roitman, Haggai  and
      Konopnicki, David",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5407",
    doi = "10.18653/v1/D19-5407",
    pages = "57--63",
}
@inproceedings{arumae-etal-2019-towards,
    title = "Towards Annotating and Creating Summary Highlights at Sub-sentence Level",
    author = "Arumae, Kristjan  and
      Bhatia, Parminder  and
      Liu, Fei",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5408",
    doi = "10.18653/v1/D19-5408",
    pages = "64--69",
}
@inproceedings{gliwa-etal-2019-samsum,
    title = "{SAMS}um Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization",
    author = "Gliwa, Bogdan  and
      Mochol, Iwona  and
      Biesek, Maciej  and
      Wawer, Aleksander",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5409",
    doi = "10.18653/v1/D19-5409",
    pages = "70--79",
}
@inproceedings{zhong-etal-2019-closer,
    title = "A Closer Look at Data Bias in Neural Extractive Summarization Models",
    author = "Zhong, Ming  and
      Wang, Danqing  and
      Liu, Pengfei  and
      Qiu, Xipeng  and
      Huang, Xuanjing",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5410",
    doi = "10.18653/v1/D19-5410",
    pages = "80--89",
}
@inproceedings{nguyen-daume-iii-2019-global,
    title = "Global Voices: Crossing Borders in Automatic News Summarization",
    author = "Nguyen, Khanh  and
      Daum{\'e} III, Hal",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5411",
    doi = "10.18653/v1/D19-5411",
    pages = "90--97",
}
@inproceedings{cho-etal-2019-multi,
    title = "Multi-Document Summarization with Determinantal Point Processes and Contextualized Representations",
    author = "Cho, Sangwoo  and
      Li, Chen  and
      Yu, Dong  and
      Foroosh, Hassan  and
      Liu, Fei",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5412",
    doi = "10.18653/v1/D19-5412",
    pages = "98--103",
}
@inproceedings{lebanoff-etal-2019-analyzing,
    title = "Analyzing Sentence Fusion in Abstractive Summarization",
    author = "Lebanoff, Logan  and
      Muchovej, John  and
      Dernoncourt, Franck  and
      Kim, Doo Soon  and
      Kim, Seokhwan  and
      Chang, Walter  and
      Liu, Fei",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5413",
    doi = "10.18653/v1/D19-5413",
    pages = "104--110",
}
@inproceedings{handler-etal-2019-summarizing,
    title = "Summarizing Relationships for Interactive Concept Map Browsers",
    author = "Handler, Abram  and
      Ganeshkumar, Premkumar  and
      O{'}Connor, Brendan  and
      AlTantawy, Mohamed",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5414",
    doi = "10.18653/v1/D19-5414",
    pages = "111--115",
}
@inproceedings{liu-chen-2019-exploiting,
    title = "Exploiting Discourse-Level Segmentation for Extractive Summarization",
    author = "Liu, Zhengyuan  and
      Chen, Nancy",
    booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5415",
    doi = "10.18653/v1/D19-5415",
    pages = "116--121",
}

repository: emorynlp/nlprankings

repo_name: emorynlp/nlprankings

gha_license_id: NOASSERTION


text:
package main

import (
	mmplugin "github.com/kaakaa/mmplugin-channel-recommender/server/plugin"
	"github.com/mattermost/mattermost-server/plugin"
)

func main() {
	plugin.ClientMain(&mmplugin.Plugin{})
}

repository: kaakaa/mmplugin-channel-recommender

repo_name: kaakaa/mmplugin-channel-recommender

extension: go