text:
;metadataPrefix=html{\&}amp;identifier=ADA547371},
year = {2011}
}
@inproceedings{Rizzo2011,
abstract = {The Web of data promotes the idea that more and more data are interconnected. A step towards this goal is to bring more structured annotations to existing documents using common vocabularies or ontologies. Semi-structured texts such as scientific, medical or news articles as well as forum and archived mailing list threads or (micro-)blog posts can hence be semantically annotated. Named Entity (NE) extractors play a key role for extracting structured information by identifying features, also called entities, and by linking them to other web resources by means of typed inferences. In this article, we propose a thorough evaluation of five popular Linked Data entity extractors which expose APIs: AlchemyAPI, DBPedia Spotlight, Extractiv, OpenCalais and Zemanta. We present NERD, an evaluation framework we have developed and the results of a controlled evaluation performed by human beings that consists in assigning a Boolean value to three criteria: entity detection, entity type and entity disambiguation.},
address = {Bonn, Germany},
annote = {Alchemy APIが精度が最も良い
URIを生成するという意味では、ZemantaやDBpedia Spotlightも良い},
author = {Rizzo, Giuseppe and Troncy, Rapha{\"{e}}l},
booktitle = {Workshop on Web Scale Knowledge Extraction (WEKEX'11)},
file = {:Users/ikuya/papers/Nerd Evaluating named entity recognition tools in the web of data - 2011 - Rizzo, Troncy.pdf:pdf},
keywords = {cessing,entity extraction,entity extraction tools,evaluation of linked data,linked data,natural language pro-},
title = {{Nerd: Evaluating named entity recognition tools in the web of data}},
url = {http://www.eurecom.fr/{~}troncy/Publications/Rizzo{\_}Troncy-wekex11.pdf http://porto.polito.it/2440793/1/wekex2011{\_}submission{\_}6.pdf},
year = {2011}
}
@article{Urbansky2011,
author = {Urbansky, David and Thom, J and Schuster, Daniel and Schill, Alexander},
file = {:Users/ikuya/papers/Training a named entity recognizer on the web - 2011 - Urbansky et al.pdf:pdf},
journal = {Web Information System {\ldots}},
pages = {87--100},
title = {{Training a named entity recognizer on the web}},
url = {http://www.springerlink.com/index/8J41577340015017.pdf},
year = {2011}
}
@inproceedings{luo-EtAl:2015:EMNLP2,
address = {Lisbon, Portugal},
author = {Luo, Gang and Huang, Xiaojiang and Lin, Chin-Yew and Nie, Zaiqing},
booktitle = {Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing},
pages = {879--888},
publisher = {Association for Computational Linguistics},
title = {{Joint Entity Recognition and Disambiguation}},
url = {https://aclweb.org/anthology/D/D15/D15-1104},
year = {2015}
}
@article{Carmel2014a,
author = {Carmel, David and Chang, Ming-Wei and Gabrilovich, Evgeniy and Hsu, Bo-June (Paul) and Wang, Kuansan},
doi = {10.1145/2701583.2701591},
issn = {01635840},
journal = {ACM SIGIR Forum},
number = {2},
pages = {63--77},
publisher = {ACM},
title = {{ERD'14: Entity Recognition and Disambiguation Challenge}},
url = {http://dl.acm.org/citation.cfm?id=2701583.2701591},
volume = {48},
year = {2014}
}
@inproceedings{Cohen2003,
abstract = {Using an open-source, Java toolkit of name-matching methods, we experimentally compare string distance metrics on the task of matching entity names. We inves- tigate a number of different metrics proposed by differ- ent communities, including edit-distance metrics, fast heuristic string comparators , token-based distance met- rics, and hybrid methods. Overall, the best-performing method is a hybrid scheme combining a TFIDF weight- ing scheme, which is widely used in information re- trieval, with the Jaro-Winkler string-distance scheme, which was developed in the probabilistic record linkage community.},
author = {Cohen, William W. and Ravikumar, Pradeep D. and Fienberg, Stephen E.},
booktitle = {Proceedings of IJCAI-03 Workshop on Information Integration on the Web},
pages = {73--78},
pmid = {21700836},
title = {{A comparison of string distance metrics for name-matching tasks}},
year = {2003}
}
@misc{Boston2013b,
abstract = {This paper presents an implemented and evaluated methodology for disambiguating terms in search queries and for augmenting queries with expansion terms. By exploiting Wikipedia articles and their reference relations, our method is able to disambiguate terms in particularly short queries with few context words and to effectively expand queries for retrieval of short documents such as tweets. Our strategy can determine when a sequence of words should be treated as a single entity rather than as a sequence of individual entities. This work is part of a larger project to retrieve information graphics in response to user queries. ?? 2013 Elsevier B.V. All rights reserved.},
author = {Boston, Christopher and Fang, Hui and Carberry, Sandra and Wu, Hao and Liu, Xitong},
booktitle = {Data and Knowledge Engineering},
keywords = {Disambiguation,Query expansion,Search queries},
title = {{Wikimantic: Toward effective disambiguation and expansion of queries}},
year = {2013}
}
@article{Hatch,
author = {Hatch, Andrew},
file = {:Users/ikuya/papers/Clickable Terms for Contextual Advertising Categories and Subject Descriptors - Unknown - Hatch.pdf:pdf},
isbn = {9781450302210},
keywords = {content match,contextual advertising},
title = {{Clickable Terms for Contextual Advertising Categories and Subject Descriptors}}
}
@inproceedings{Shen2013,
address = {New York, New York, USA},
author = {Shen, Wei and Wang, Jianyong and Luo, Ping and Wang, Min},
booktitle = {Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13},
doi = {10.1145/2487575.2487686},
isbn = {9781450321747},
keywords = {knowledge base,tweet entity linking,user interest modeling},
month = {aug},
pages = {68},
publisher = {ACM Press},
title = {{Linking named entities in Tweets with knowledge base via user interest modeling}},
url = {http://dl.acm.org/citation.cfm?id=2487575.2487686},
year = {2013}
}
@inproceedings{Trofimov2012,
address = {New York, New York, USA},
author = {Trofimov, Ilya and Kornetova, Anna and Topinskiy, Valery},
booktitle = {Proceedings of the Sixth International Workshop on Data Mining for Online Advertising and Internet Economy - ADKDD '12},
doi = {10.1145/2351356.2351358},
file = {:Users/ikuya/papers/Using boosted trees for click-through rate prediction for sponsored search - 2012 - Trofimov, Kornetova, Topinskiy.pdf:pdf},
isbn = {9781450315456},
month = {aug},
pages = {1--6},
publisher = {ACM Press},
title = {{Using boosted trees for click-through rate prediction for sponsored search}},
url = {http://dl.acm.org/citation.cfm?id=2351356.2351358},
year = {2012}
}
@article{Chung,
author = {Chung, Sung H},
file = {:Users/ikuya/papers/The Impact of Images on User Clicks in Product Search - Unknown - Chung.pdf:pdf},
isbn = {9781450315562},
keywords = {click prediction,image features,online shopping,product search ranking,vertical search},
title = {{The Impact of Images on User Clicks in Product Search}}
}
@article{Westerski2009,
author = {Westerski, Adam},
file = {:Users/ikuya/papers/Integrated Environment for Visual Data-Level Mashup Development - 2009 - Westerski.pdf:pdf},
journal = {Web Information Systems Engineering-WISE 2009},
keywords = {integration,linked,mashup,semantic web,tool,web development},
pages = {481--487},
publisher = {Springer},
title = {{Integrated Environment for Visual Data-Level Mashup Development}},
url = {http://www.springerlink.com/index/LQ36G5461160UN5L.pdf},
year = {2009}
}
@inproceedings{Guo2009,
address = {New York, New York, USA},
author = {Guo, Jiafeng and Xu, Gu and Cheng, Xueqi and Li, Hang},
booktitle = {Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '09},
doi = {10.1145/1571941.1571989},
isbn = {9781605584836},
keywords = {named entity recognition,topic model},
month = {jul},
pages = {267},
publisher = {ACM Press},
title = {{Named entity recognition in query}},
url = {http://dl.acm.org/citation.cfm?id=1571941.1571989},
year = {2009}
}
@inproceedings{Ennals2007,
author = {Ennals, Rob and Gay, David},
booktitle = {ACM SIGPLAN Notices},
doi = {10.1145/1291220.1291187},
file = {:Users/ikuya/papers/User-friendly functional programming for web mashups - 2007 - Ennals, Gay.pdf:pdf},
issn = {03621340},
keywords = {and wikimapia,at the time of,browser,com,com which combines,com with slashdot,digg,end-user,mashup,org,org with google maps,physical locations,programmableweb,to provide information about,web,wikipedia,writing},
month = {oct},
number = {9},
pages = {223},
title = {{User-friendly functional programming for web mashups}},
url = {http://portal.acm.org/citation.cfm?doid=1291220.1291187},
volume = {42},
year = {2007}
}
@inproceedings{Nestler2008,
author = {Nestler, Tobias},
booktitle = {Proceedings of the 10th international Conference on information integration and Web-Based Applications $\backslash${\&} Services},
file = {:Users/ikuya/papers/Towards a mashup-driven end-user programming of SOA-based applications - 2008 - Nestler.pdf:pdf},
keywords = {lightweight processing,mashups,presentation oriented service composition,tegration,ui in-},
pages = {551--554},
publisher = {ACM},
title = {{Towards a mashup-driven end-user programming of SOA-based applications}},
url = {http://portal.acm.org/citation.cfm?id=1497308.1497408},
year = {2008}
}
@inproceedings{VonBrzeski2007,
annote = {- Abstract

検索のクエリログを利用。

評価指標：
* Accuracy
* Interestingness
* Relevance

周辺のコンテキストを利用すると精度が向上する。

1,586のエンティティを1519のドキュメントから抽出して評価した。

- Introduction

Entity detectionは主に機械（ユーザでない）から利用されてきた。
Intelligent hyperlinksを生成するシステムが増えている(IntelliTXT, Vibrant Media, Kontera, Ontok, Y! Shortcuts)
-{\&}gt; User-Centric Entity Detection Systems

評価には量だけでなく質が必要になる。

* 文書のトピックに準拠していないといけない
* キーワード内にキーワードが含まれている可能性がある
-{\&}gt; Betty Crocker's famous cheesecakeでBetty Crockerを抽出してはいけない。

評価指標：
* Accuracy
* Interestingness
* Relevanceで評価

Concept extension: under-selectionを防ぐ
-{\&}gt; Garlandをマークアップ
-{\&}gt; Garland, TexasではなくKelly Garlandに拡張する

ドキュメントからConcept vectorを生成
-{\&}gt; entityとconceptをrelevanceで並び替えたvector

Concepｔ Vectorをconcept extensionのアルゴリズムで解析

Contextual Shortcutsでデモンストレーション

- Related Work
* Named Entity Recognition
* User-centric entity detection systems
-{\&}gt; ルールベースのモノ
-{\&}gt; In-text ad
-{\&}gt; SmartTags

- Contextual Shortcuts(システム概要)
下記が含まれる
* Pre-processing
* Entity detection
* Post-processing
* Generating a concept vector
* Finding concept extensions

-- Pre-processing
HTMLやテキストを処理
文と段落を認識
-- Entity detection
detectorがpluggableに追加できるようになっている

* 正規表現ベース
-{\&}gt;電話番号/URL/E-mail
* Location detector
* Keyword Detector

-{\&}gt; surrounding context(周辺トークン)と一緒に次のステップに渡される

Location detectorとKeyword detectorはpreloadのdata-packsがメモリに必要

独自のエンティティのタクソノミを用いている
/places
/places/{\&}lt;country code{\&}gt;/country
/places/{\&}lt;country code{\&}gt;/town
/identifier
/identifier/URL

など

Keyword detectionには上記タクソノミに基づく辞書を利用
265,000エンテティが120のタイプに分類されている
キーワードは複数の分類に属すことができる

Locationの検出にgeo-spatial dataを用いている。住所や地名などを検出可能

エンティティにdata-packを使って、taxonomyのtypeやその他メタデータ（緯度経度など）を結びつける

Regular expression系のdetectorの精度は高いため、Keyword detectorの精度をどのようにあげるかに注力した。

editorially reviewedなterms/phrasesを超えた精度の実現のため、サーチログを用いることとした。

* Generating a concept vector
(1) TF-IDFでドキュメントからterm vectorを作る
(2) Unit vectorをquery logから検出し作る
→正規化され全てのベクトル値は0～1までになる
(3) Term vectorとunit vectorを統合しconcept vectorを作成する

* Unit vectorはquery logから生成されており、interestingnessをcaptureしている。
* term vectorはTF-IDFをコーパスに対して取っており、relevanceをcaptureしている。
-{\&}gt; mergeすることで、interestingnessとrelevanceを双方計測していることになる。

* Finding concept extensions
accuracyを高めるために、underselectionを防ぐ

-- Post-processing
* Collision Detection
* Filtering
Concept vectorのweightが低いものとblack list、stop words等の単語を削除する。
* Annotation
JSONやXMLに変換する},
author = {von Brzeski, Vadim and Irmak, Utku and Kraft, Reiner},
booktitle = {Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management (CIKM '07)},
file = {:Users/ikuya/papers/Leveraging context in user-centric entity detection systems - 2007 - von Brzeski, Irmak, Kraft.pdf:pdf},
keywords = {Yahoo! shortcuts,con-,content syndication,contextual,contextual shortcuts,data detector,entity detection,information extraction,text},
mendeley-tags = {Yahoo! shortcuts,data detector,entity detection},
pages = {691--700},
title = {{Leveraging context in user-centric entity detection systems}},
url = {http://portal.acm.org/citation.cfm?id=1321537 http://dl.acm.org/citation.cfm?id=1321537},
year = {2007}
}
@inproceedings{Pantel2011,
author = {Pantel, Patrick and Fuxman, Ariel},
booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (HLT '11)},
file = {:Users/ikuya/papers/Jigs and lures associating web queries with structured entities - 2011 - Pantel, Fuxman.pdf:pdf},
isbn = {978-1-932432-87-9},
pages = {83--92},
title = {{Jigs and lures: associating web queries with structured entities}},
url = {http://dl.acm.org/citation.cfm?id=2002472.2002484},
volume = {1},
year = {2011}
}
@article{Le2004,
author = {Le, Zhang},
file = {:Users/ikuya/papers/Maximum Entropy Modeling Toolkit for Python and C - 2004 - Le.pdf:pdf},
number = {December},
title = {{Maximum Entropy Modeling Toolkit for Python and C ++}},
year = {2004}
}
@article{Kim2009,
author = {Kim, Jin-Suk and Jin, Du-Seok and Kim, Kwang-Young and Choe, Ho-Seop},
doi = {10.3745/JIPS.2009.5.3.159},
file = {:Users/ikuya/papers/Automatic In-Text Keyword Tagging based on Information Retrieval - 2009 - Kim et al.pdf:pdf},
issn = {1976-913X},
journal = {Journal of Information Processing Systems},
keywords = {automatic in-text keyword tagging,boyer-moore-,cross-referencing,horspool algorithm,in-text content link,information retrieval,keyword dictionary,pattern matching},
month = {sep},
number = {3},
pages = {159--166},
title = {{Automatic In-Text Keyword Tagging based on Information Retrieval}},
url = {http://koreascience.or.kr/journal/view.jsp?issn=1976-913X{\&}vol=5{\&}no=3{\&}sp=159},
volume = {5},
year = {2009}
}
@article{Gardner2009,
author = {Gardner, J. and Krowne, a. and Xiong, L.},
doi = {10.1109/TKDE.2008.136},
file = {:Users/ikuya/papers/NNexus An Automatic Linker for Collaborative Web-Based Corpora - 2009 - Gardner, Krowne, Xiong.pdf:pdf},
issn = {1041-4347},
journal = {IEEE Transactions on Knowledge and Data Engineering},
month = {jun},
number = {6},
pages = {829--839},
title = {{NNexus: An Automatic Linker for Collaborative Web-Based Corpora}},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4564462},
volume = {21},
year = {2009}
}
@techreport{export:156194,
abstract = {
This paper presents a method for entity disambiguation, one of the most
substantial tasks for machines to understand text in natural languages. In a
natural language, terms have ambiguity, e.g. "Barcelona" usually means a Spanish
city but it can also refer to a professional football club. In our work, we
utilize a probabilistic taxonomy that is as rich as our mental world in terms of
the concepts of worldly facts it contains. We then employ a naive Bayes
probabilistic model to disambiguate a term by identifying its related terms in
the same document. Specifically, our method consists of two steps: clustering
related terms and conceptualizing the cluster using the probabilistic taxonomy.
We cluster related terms probabilistically instead of using any threshold-based
deterministic clustering approach. Our method automatically adjusts the relevance
weight between two terms by taking the topic of the document into consideration.
This enables us to perform clustering without using a sensitive, predefined
threshold. Then, we conceptualize all possible clusters using the probabilistic
taxonomy, and we aggregate the probabilities of each concept to find the most
likely one. Experimental results show that our method outperforms threshold-based
methods with optimally set thresholds as well as several gold standard approaches
for entity disambiguation.
},
author = {Shirakawa, Masumi and Wang, Haixun and Song, Yangqiu and Wang, Zhongyuan and Nakayama, Kotaro and Hara, Takahiro},
number = {MSR-TR-2011-125},
title = {{Entity Disambiguation based on a Probabilistic Taxonomy}},
url = {http://research.microsoft.com/apps/pubs/default.aspx?id=156194},
year = {2011}
}
@article{Dakka2008,
author = {Dakka, Wisam and Cucerzan, S},
file = {:Users/ikuya/papers/Augmenting wikipedia with named entity tags - 2008 - Dakka, Cucerzan.pdf:pdf},
journal = {Proceedings of the 3rd International Joint {\ldots}},
pages = {545--552},
title = {{Augmenting wikipedia with named entity tags}},
url = {https://www.aclweb.org/anthology-new/I/I08/I08-1071.pdf},
year = {2008}
}
@inproceedings{Zhou2001,
address = {Morristown, NJ, USA},
author = {Zhou, GuoDong and Su, Jian},
booktitle = {Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL '02},
doi = {10.3115/1073083.1073163},
file = {:Users/ikuya/papers/Named entity recognition using an HMM-based chunk tagger - 2001 - Zhou, Su.pdf:pdf},
keywords = {HMM,named entity detection},
mendeley-tags = {HMM,named entity detection},
month = {jul},
pages = {473},
publisher = {Association for Computational Linguistics},
title = {{Named entity recognition using an HMM-based chunk tagger}},
url = {http://dl.acm.org/citation.cfm?id=1073083.1073163},
year = {2001}
}
@article{Daiber2011,
author = {Daiber, Joachim},
file = {:Users/ikuya/papers/Candidate Selection and Evaluation in the DBpedia Spotlight Entity Extraction System - 2011 - Daiber.pdf:pdf},
number = {4232126},
title = {{Candidate Selection and Evaluation in the DBpedia Spotlight Entity Extraction System}},
year = {2011}
}
@article{Mohan2011a,
abstract = {In May 2010 Yahoo! Inc. hosted the Learning to Rank Challenge. This paper summarizes the approach by the highly placed team Washington University in St. Louis. We investigate Random Forests (RF) as a low-cost alternative algorithm to Gradient Boosted Regression Trees (GBRT) (the de facto standard of web-search ranking). We demonstrate that it yields surprisingly accurate ranking results | comparable to or better than GBRT. We combine the two algorithms by rst learning a ranking function with RF and using it as initialization for GBRT. We refer to this setting as iGBRT. Following a recent discussion by Li et al. (2007), we show that the results of iGBRT can be improved upon even further when the web-search ranking task is cast as classi cation instead of regression. We provide an upper bound of the Expected Reciprocal Rank (Chapelle et al., 2009) in terms of classi cation error and demonstrate that iGBRT outperforms GBRT and RF on the Microsoft Learning to Rank and Yahoo Ranking Competition data sets with surprising consistency.},
author = {Mohan, Ananth and Chen, Zheng and Weinberger, KQ},
file = {:Users/ikuya/papers/Web-search ranking with initialized gradient boosted regression trees - 2011 - Mohan, Chen, Weinberger.pdf:pdf},
journal = {Journal of Machine Learning Research},
keywords = {boosting,decision trees,random forests,ranking},
pages = {77--89},
title = {{Web-search ranking with initialized gradient boosted regression trees}},
url = {http://www1.cse.wustl.edu/{~}kilian/papers/mohan11a.pdf},
volume = {14},
year = {2011}
}
@inproceedings{Dredze2010,
author = {Dredze, Mark and McNamee, Paul and Rao, Delip and Gerber, Adam and Finin, Tim},
booktitle = {Proceedings of the 23rd International Conference on Computational Linguistics (COLING '10)},
file = {:Users/ikuya/papers/Entity disambiguation for knowledge base population - 2010 - Dredze et al.pdf:pdf},
pages = {277--285},
title = {{Entity disambiguation for knowledge base population}},
url = {http://dl.acm.org/citation.cfm?id=1873813},
year = {2010}
}
@inproceedings{weston-EtAl:2013:EMNLP,
address = {Seattle},
author = {Weston, Jason and Bordes, Antoine and Yakhnenko, Oksana and Usunier, Nicolas},
booktitle = {Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing},
pages = {1366--1371},
publisher = {Association for Computational Linguistics},
title = {{Connecting Language and Knowledge Bases with Embedding Models for Relation Extraction}},
url = {http://www.aclweb.org/anthology/D13-1136},
year = {2013}
}
@inproceedings{chen-demelo:2015:VSM-NLP,
address = {Denver},
author = {Chen, Jiaqiang and de Melo, Gerard},
booktitle = {Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing},
pages = {168--175},
publisher = {Association for Computational Linguistics},
title = {{Semantic Information Extraction for Improved Word Embeddings}},
url = {http://www.aclweb.org/anthology/W15-1523},
year = {2015}
}
@article{Bizer2009a,
author = {Bizer, Christian and Heath, Tom and Berners-Lee, Tim},
doi = {10.4018/jswis.2009081901},
issn = {1552-6283},
journal = {International Journal on Semantic Web and Information Systems},
language = {en},
number = {3},
pages = {1--22},
publisher = {IGI Global},
title = {{Linked Data - The Story So Far}},
url = {http://www.igi-global.com/article/linked-data-story-far/37496},
volume = {5},
year = {2009}
}
@inproceedings{Carmel2014,
author = {Carmel, David and Chang, Ming-Wei and Gabrilovich, Evgeniy and Hsu, Bo-June (Paul) and Wang, Kuansan},
booktitle = {Proceedings of the 37th International ACM SIGIR Conference on Research {\&} Development in Information Retrieval (SIGIR '14)},
doi = {10.1145/2600428.2600734},
isbn = {9781450322577},
keywords = {entity disambiguation,entity linking},
pages = {1292--1292},
title = {{ERD'14}},
url = {http://dl.acm.org/citation.cfm?id=2600428.2600734},
year = {2014}
}
@inproceedings{Kong2013,
address = {New York, New York, USA},
author = {Kong, Weize and Aktolga, Elif and Allan, James},
booktitle = {Proceedings of the 22nd ACM international conference on Conference on information {\&} knowledge management - CIKM '13},
doi = {10.1145/2505515.2505719},
file = {:Users/ikuya/papers/Improving passage ranking with user behavior information - 2013 - Kong, Aktolga, Allan.pdf:pdf},
isbn = {9781450322638},
keywords = {randomforest},
mendeley-tags = {randomforest},
month = {oct},
pages = {1999--2008},
publisher = {ACM Press},
title = {{Improving passage ranking with user behavior information}},
url = {http://dl.acm.org/citation.cfm?id=2541176.2505719},
year = {2013}
}
@inproceedings{Yazdani2013,
abstract = {We propose a method for computing semantic relatedness between words or texts by using knowledge from hypertext encyclopedias such as Wikipedia. A network of concepts is built by filtering the encyclopedias articles, each concept corresponding to an article. Two types of weighted links between concepts are considered: one based on hyperlinks between the texts of the articles, and another one based on the lexical similarity between them. We propose and implement an efficient random walk algorithm that computes the distance between nodes, and then between sets of nodes, using the visiting probability from one (set of) node(s) to another. Moreover, to make the algorithm tractable, we propose and validate empirically two truncation methods, and then use an embedding space to learn an approximation of visiting probability. To evaluate the proposed distance, we apply our method to four important tasks in natural language processing: word similarity, document similarity, document clustering and classification, and ranking in information retrieval. The performance of the method is state-of-the-art or close to it for each task, thus demonstrating the generality of the knowledge resource. Moreover, using both hyperlinks and lexical similarity links improves the scores with respect to a method using only one of them, because hyperlinks bring additional real-world knowledge not captured by lexical similarity. ?? 2012 Elsevier B.V. All rights reserved.},
author = {Yazdani, Majid and Popescu-Belis, Andrei},
booktitle = {IJCAI International Joint Conference on Artificial Intelligence},
pages = {3185--3189},
title = {{Computing text semantic relatedness using the contents and links of a hypertext encyclopedia}},
year = {2013}
}
@inproceedings{Ji2011,
author = {Ji, Heng and Grishman, Ralph and Dang, Hoa Trang},
booktitle = {Proceeding of Text Analysis Conference (TAC)},
file = {:Users/ikuya/papers/Overview of the TAC 2011 Knowledge Base Population Track - 2011 - Ji, Grishman, Trang Dang.pdf:pdf},
isbn = {1117458812938},
title = {{Overview of the TAC2011 knowledge base population track}},
year = {2011}
}
@article{Daniel2009a,
author = {Daniel, Florian and Matera, Maristella},
file = {:Users/ikuya/papers/Turning Web Applications into Mashup Components Issues, Models, and Solutions - 2009 - Daniel, Matera.pdf:pdf},
journal = {Web Engineering},
pages = {45--60},
publisher = {Springer},
title = {{Turning Web Applications into Mashup Components: Issues, Models, and Solutions}},
url = {http://www.springerlink.com/index/Y8P761P023614P98.pdf},
year = {2009}
}
@inproceedings{Wick2013,
address = {New York, New York, USA},
author = {Wick, Michael and Singh, Sameer and Pandya, Harshal and McCallum, Andrew},
booktitle = {Proceedings of the 2013 workshop on Automated knowledge base construction - AKBC '13},
doi = {10.1145/2509558.2509570},
file = {:Users/ikuya/papers/A joint model for discovering and linking entities - 2013 - Wick et al.pdf:pdf},
isbn = {9781450324113},
keywords = {coreference,entity linking,entity resolution},
month = {oct},
pages = {67--72},
publisher = {ACM Press},
title = {{A joint model for discovering and linking entities}},
url = {http://dl.acm.org/citation.cfm?id=2509558.2509570},
year = {2013}
}
@inproceedings{Cheng2010,
address = {New York, New York, USA},
author = {Cheng, Haibin and Cant{\'{u}}-Paz, Erick},
booktitle = {Proceedings of the third ACM international conference on Web search and data mining - WSDM '10},
doi = {10.1145/1718487.1718531},
file = {:Users/ikuya/papers/Personalized click prediction in sponsored search - 2010 - Cheng, Cant{\'{u}}-Paz.pdf:pdf},
isbn = {9781605588896},
month = {feb},
pages = {351},
publisher = {ACM Press},
title = {{Personalized click prediction in sponsored search}},
url = {http://dl.acm.org/citation.cfm?id=1718487.1718531},
year = {2010}
}
@inproceedings{Konig2009,
address = {New York, New York, USA},
author = {K{\"{o}}nig, Arnd Christian and Gamon, Michael and Wu, Qiang},
booktitle = {Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '09},
doi = {10.1145/1571941.1572002},
isbn = {9781605584836},
month = {jul},
pages = {347},
publisher = {ACM Press},
title = {{Click-through prediction for news queries}},
url = {http://dl.acm.org/citation.cfm?id=1571941.1572002},
year = {2009}
}
@inproceedings{Ennals2007a,
author = {Ennals, R.J. and Garofalakis, M.N.},
booktitle = {Proceedings of the 2007 ACM SIGMOD international conference on Management of data},
file = {:Users/ikuya/papers/MashMaker mashups for the masses - 2007 - Ennals, Garofalakis.pdf:pdf},
keywords = {end-users,mashup,web},
pages = {1118},
publisher = {ACM},
title = {{MashMaker: mashups for the masses}},
url = {http://portal.acm.org/citation.cfm?id=1247480.1247626},
year = {2007}
}
@article{Liu2012,
author = {Liu, Xiaohua and Zhou, Ming and Wei, Furu and Fu, Zhongyang and Zhou, Xiangyang},
file = {:Users/ikuya/papers/Joint inference of named entity recognition and normalization for tweets - 2012 - Liu et al.pdf:pdf},
month = {jul},
pages = {526--535},
publisher = {Association for Computational Linguistics},
title = {{Joint inference of named entity recognition and normalization for tweets}},
url = {http://dl.acm.org/citation.cfm?id=2390524.2390598},
year = {2012}
}
@inproceedings{Han2010a,
address = {New York, New York, USA},
author = {Han, Hao and Guo, Junxia and Tokuda, Takehiro},
booktitle = {Proceedings of the 19th international conference on World wide web - WWW '10},
doi = {10.1145/1772690.1772828},
file = {:Users/ikuya/papers/Deep mashup - 2010 - Han, Guo, Tokuda.pdf:pdf},
isbn = {9781605587998},
keywords = {figure 1,mashup,the outline of deep,web application,web feed,web service},
pages = {1109},
publisher = {ACM Press},
title = {{Deep mashup}},
url = {http://portal.acm.org/citation.cfm?doid=1772690.1772828},
year = {2010}
}
@article{Sabbouh2007,
address = {New York, New York, USA},
author = {Sabbouh, Marwan and Higginson, Jeff and Semy, Salim and Gagne, Danny},
doi = {10.1145/1242572.1242821},
file = {:Users/ikuya/papers/Web mashup scripting language - 2007 - Sabbouh et al.pdf:pdf},
isbn = {9781595936547},
journal = {Proceedings of the 16th international conference on World Wide Web - WWW '07},
pages = {1305},
publisher = {ACM Press},
title = {{Web mashup scripting language}},
url = {http://portal.acm.org/citation.cfm?doid=1242572.1242821},
year = {2007}
}
@inproceedings{Tsuruoka2011,
author = {Tsuruoka, Yoshimasa and Miyao, Y. and Kazama, J.},
booktitle = {Proceedings of the Fifteenth Conference on Computational Natural Language Learning},
file = {:Users/ikuya/papers/Learning with lookahead can history-based models rival globally optimized models - 2011 - Tsuruoka, Miyao, Kazama.pdf:pdf},
number = {June},
pages = {238--246},
publisher = {Association for Computational Linguistics},
title = {{Learning with lookahead: can history-based models rival globally optimized models?}},
url = {http://www.aclweb.org/anthology/W/W11/W11-0328.pdf},
year = {2011}
}
@article{Turian2010,
author = {Turian, Joseph and Ratinov, Lev},
file = {:Users/ikuya/papers/Word representations a simple and general method for semi-supervised learning - 2010 - Turian, Ratinov.pdf:pdf},
journal = {Proceedings of the 48th Annual Meeting},
title = {{Word representations: a simple and general method for semi-supervised learning}},
url = {http://dl.acm.org/citation.cfm?id=1858721},
year = {2010}
}
@article{Gutlein2009,
author = {Gutlein, Martin and Frank, Eibe},
doi = {10.1109/CIDM.2009.4938668},
file = {:Users/ikuya/papers/Large-scale attribute selection using wrappers - 2009 - Gutlein, Frank.pdf:pdf},
isbn = {978-1-4244-2765-9},
journal = {{\ldots} Intelligence and Data {\ldots}},
month = {mar},
pages = {332--339},
publisher = {Ieee},
title = {{Large-scale attribute selection using wrappers}},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4938668 http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=4938668},
year = {2009}
}
@inproceedings{Zheng2010,
annote = {- Named Entity LinkingにLearning to Rankを使用
- Learning to Rank(ListNet, Ranking Perceptron)でランキングし、最上位のエントリが正しいかどうか(NILでないか)をSVMで判定
- 特徴量前処理:
  - Stanford NERで全てのNEを抽出
  - 国名・都市名を手動辞書で抽出
- Learning to Rankの特徴量
  - Surface: テキストの一致度・クエリとの一致度など
  - Context: TF-IDFの一致度・固有表現の一致度
  - Special: 都市名・国名・NERの型の一致など
- SVMの特徴量
  - Learning to Rankで用いた特徴量
  - Learning to Rankでのスコア
  - クエリの単語がWikipediaに全て含まれているか
　など},
author = {Zheng, Zhicheng and Li, Fangtao and Huang, Minlie and Zhu, Xiaoyan},
booktitle = {Proceedings of the 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL HLT '13)},
file = {:Users/ikuya/papers/Learning to link entities with knowledge base - 2010 - Zheng et al(2).pdf:pdf},
pages = {483--491},
title = {{Learning to link entities with knowledge base}},
url = {http://dl.acm.org/citation.cfm?id=1858071},
year = {2010}
}
@inproceedings{Heo2011,
address = {New York, New York, USA},
author = {Heo, Seongkook and Lee, Geehyuk},
booktitle = {Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services - MobileHCI '11},
doi = {10.1145/2037373.2037393},
file = {:Users/ikuya/papers/Forcetap - 2011 - Heo, Lee.pdf:pdf},
isbn = {9781450305419},
keywords = {built-in accelerometer,force sensing,mobile devices,pressure input,single-handed interaction,tap input,touch screen},
month = {aug},
pages = {113},
publisher = {ACM Press},
title = {{Forcetap}},
url = {http://dl.acm.org/citation.cfm?id=2037373.2037393},
year = {2011}
}
@article{He2010,
author = {He, Jiyin and Rijke, Maarten De},
file = {:Users/ikuya/papers/A ranking approach to target detection for automatic link generation - 2010 - He, Rijke.pdf:pdf},
isbn = {9781605588964},
journal = {Proceeding of the 33rd international ACM SIGIR {\ldots}},
keywords = {disambiguation,learning to rank,link generation,wi-},
number = {iii},
pages = {831--832},
title = {{A ranking approach to target detection for automatic link generation}},
url = {http://dl.acm.org/citation.cfm?id=1835638},
year = {2010}
}
@incollection{houlsby2014scalable,
author = {Houlsby, Neil and Ciaramita, Massimiliano},
booktitle = {Advances in Information Retrieval},
pages = {335--346},
publisher = {Springer},
title = {{A scalable gibbs sampler for probabilistic entity linking}},
year = {2014}
}
@inproceedings{Hoffart2011,
author = {Hoffart, Johannes and Yosef, Mohamed Amir and Bordino, Ilaria and F{\"{u}}rstenau, Hagen and Pinkal, Manfred and Spaniol, Marc and Taneva, Bilyana and Thater, Stefan and Weikum, Gerhard},
booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)},
file = {:Users/ikuya/papers/Robust Disambiguation of Named Entities in Text - 2011 - Hoffart et al.pdf:pdf},
isbn = {978-1-937284-11-4},
pages = {782--792},
title = {{Robust Disambiguation of Named Entities in Text}},
url = {http://dl.acm.org/citation.cfm?id=2145432.2145521},
year = {2011}
}
@article{Mendes2011a,
author = {Mendes, PN and Daiber, Joachim},
file = {:Users/ikuya/papers/Evaluating dbpedia spotlight for the tac-kbp entity linking task - 2011 - Mendes, Daiber.pdf:pdf},
journal = {Proceedings of the {\ldots}},
pages = {1--4},
title = {{Evaluating dbpedia spotlight for the tac-kbp entity linking task}},
url = {http://www.wiwiss.fu-berlin.de/en/institute/pwo/bizer/research/publications/Mendes-Daiber-Jakob-Bizer-DBpediaSpotlight-TACKBP2011.pdf},
year = {2011}
}
@inproceedings{Han2012,
author = {Han, Xianpei and Sun, L},
booktitle = {Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL '12)},
file = {:Users/ikuya/papers/An entity-topic model for entity linking - 2012 - Han, Sun.pdf:pdf},
pages = {105--115},
title = {{An entity-topic model for entity linking}},
url = {http://dl.acm.org/citation.cfm?id=2390962},
year = {2012}
}
@inproceedings{Spitkovsky2012,
abstract = {We present a resource for automatically associating strings of text with English Wikipedia concepts. Our machinery is bi-directional, in the sense that it uses the same fundamental probabilistic methods to map strings to empirical distributions over Wikipedia articles as it does to map article URLs to distributions over short, language-independent strings of natural language text. For maximal inter- operability, we release our resource as a set of flat line-based text files, lexicographically sorted and encoded with UTF-8. These files capture joint probability distributions underlying concepts (we use the terms article, concept andWikipedia URL interchangeably) and associated snippets of text, aswell as other features that can come in handy whenworkingwithWikipedia articles and related information.},
author = {Spitkovsky, Valentin I and Chang, Angel X},
booktitle = {International Conference on Language Resources and Evaluation},
keywords = {clir,cross-language information retrieval,el,entity linking,wikipedia},
pages = {3168--3175},
title = {{A Cross-Lingual Dictionary for English Wikipedia Concepts}},
url = {http://www.lrec-conf.org/proceedings/lrec2012/pdf/266{\_}Paper.pdf},
year = {2012}
}
@article{Milne2013,
author = {Milne, David and Witten, Ian H.},
doi = {10.1016/j.artint.2012.06.007},
file = {:Users/ikuya/papers/An open-source toolkit for mining Wikipedia - 2013 - Milne, Witten.pdf:pdf},
issn = {00043702},
journal = {Artificial Intelligence},
pages = {222--239},
publisher = {Elsevier B.V.},
title = {{An open-source toolkit for mining Wikipedia}},
url = {http://linkinghub.elsevier.com/retrieve/pii/S000437021200077X},
volume = {194},
year = {2013}
}
@inproceedings{Pilz2011a,
address = {New York, New York, USA},
author = {Pilz, Anja and Paa{\ss}, Gerhard},
booktitle = {Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11},
doi = {10.1145/2063576.2063700},
isbn = {9781450307178},
keywords = {classification,named entities,named entity disambiguation,named entity resolution,topic modeling},
month = {oct},
pages = {857},
publisher = {ACM Press},
title = {{From names to entities using thematic context distance}},
url = {http://dl.acm.org/citation.cfm?id=2063576.2063700},
year = {2011}
}
@inproceedings{Simmen2008,
author = {Simmen, D.E. and Altinel, M and Markl, V and Padmanabhan, S. and Singh, A},
booktitle = {Proceedings of the 2008 ACM SIGMOD international conference on Management of data},
file = {:Users/ikuya/papers//Damia data mashups for intranet applications - 2008 - Simmen et al.pdf:pdf},
pages = {1171--1182},
publisher = {ACM},
title = {{Damia: data mashups for intranet applications}},
url = {http://portal.acm.org/citation.cfm?id=1376734},
volume = {pages},
year = {2008}
}
@inproceedings{Ceccarelli2013a,
author = {Ceccarelli, Diego and Lucchese, Claudio and Orlando, Salvatore and Perego, Raffaele and Trani, Salvatore},
booktitle = {Proceedings of the Sixth International Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR '13)},
doi = {10.1145/2513204.2513212},
file = {:Users/ikuya/papers/Dexter an open source framework for entity linking - 2013 - Ceccarelli et al.pdf:pdf},
isbn = {9781450324137},
keywords = {annotations,entity linking,evaluation},
pages = {17--20},
title = {{Dexter: an open source framework for entity linking}},
url = {http://dl.acm.org/citation.cfm?id=2513204.2513212},
year = {2013}
}
@article{Wang2009,
address = {New York, New York, USA},
author = {Wang, Guiling and Yang, Shaohua and Han, Yanbo},
doi = {10.1145/1526709.1526825},
file = {:Users/ikuya/papers/Mashroom - 2009 - Wang, Yang, Han.pdf:pdf},
isbn = {9781605584874},
journal = {Proceedings of the 18th international conference on World wide web - WWW '09},
keywords = {end-user programming,mashup,nested table,spreadsheet},
pages = {861},
publisher = {ACM Press},
title = {{Mashroom}},
url = {http://portal.acm.org/citation.cfm?doid=1526709.1526825},
year = {2009}
}
@article{Zheng2013,
address = {New York, NY},
author = {Zheng, Qian and Li, Juanzi and Wang, Zhichun and Hou, Lei},
doi = {10.1007/978-1-4614-6880-6},
editor = {Li, Juanzi and Qi, Guilin and Zhao, Dongyan and Nejdl, Wolfgang and Zheng, Hai-Tao},
file = {:Users/ikuya/papers/Co-mention and Context-Based Entity Linking - 2013 - Zheng et al.pdf:pdf},
isbn = {978-1-4614-6879-0},
publisher = {Springer New York},
series = {Springer Proceedings in Complexity},
title = {{Co-mention and Context-Based Entity Linking}},
url = {http://link.springer.com/10.1007/978-1-4614-6880-6},
year = {2013}
}
@inproceedings{Jin2014,
address = {New York, New York, USA},
author = {Jin, Yuzhe and Kıcıman, Emre and Wang, Kuansan and Loynd, Ricky},
booktitle = {Proceedings of the 7th ACM international conference on Web search and data mining - WSDM '14},
doi = {10.1145/2556195.2556230},
isbn = {9781450323512},
keywords = {phrase language model,sparsity,tail entity linking,unknown entity,web-scale system},
month = {feb},
pages = {453--462},
publisher = {ACM Press},
title = {{Entity linking at the tail}},
url = {http://dl.acm.org/citation.cfm?id=2556195.2556230},
year = {2014}
}
@inproceedings{Finkel2005,
address = {Morristown, NJ, USA},
author = {Finkel, Jenny Rose and Grenager, Trond and Manning, Christopher},
booktitle = {Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL '05},
doi = {10.3115/1219840.1219885},
file = {:Users/ikuya/papers/Incorporating non-local information into information extraction systems by Gibbs sampling - 2005 - Finkel, Grenager, Manning.pdf:pdf},
month = {jun},
pages = {363--370},
publisher = {Association for Computational Linguistics},
title = {{Incorporating non-local information into information extraction systems by Gibbs sampling}},
url = {http://dl.acm.org/citation.cfm?id=1219840.1219885},
year = {2005}
}
@inproceedings{Yerva2013a,
abstract = {Pervasive web and social networks are becoming part of everyone's life. Users through their activities on these networks are leaving traces of their expertise, interests and personalities. With the advances in Web mining and user modeling techniques it is possible to leverage the user social network activity history to extract the semantics of user-generated content. In this work we explore various techniques for constructing user profiles based on the content they publish on social networks. We further show that one of the advantages of maintaining social network user profiles is to provide the context for better understanding of microposts. We propose and experimentally evaluate different approaches for entity disambiguation in social networks based on syntactic and semantic features on top of two different social networks: a general-interest network (i.e., Twitter) and a domain-specific network (i.e., StackOverflow). We demonstrate how disambiguation accuracy increases when considering enriched user profiles integrating content from both social networks.},
author = {Yerva, Surender Reddy and Catasta, Michele and Demartini, Gianluca and Aberer, Karl},
booktitle = {Proceedings of the 2013 IEEE 14th International Conference on Information Reuse and Integration, IEEE IRI 2013},
pages = {120--128},
publisher = {IEEE Computer Society},
title = {{Entity disambiguation in tweets leveraging user social profiles}},
year = {2013}
}
@article{Chen2014,
author = {Chen, Zheng and Sun, Jian-tao and Huang, Xuedong},
file = {:Users/ikuya/papers/Web Information at Your Fingertips Paper as an Interaction Metaphor - 2014 - Chen, Sun, Huang.pdf:pdf},
title = {{Web Information at Your Fingertips: Paper as an Interaction Metaphor}},
year = {2014}
}
@inproceedings{Sil2012,
abstract = {Existing techniques for disambiguating named entities in text mostly focus on Wikipedia as a target catalog of entities. Yet for many types of entities, such as restaurants and cult movies, relational databases exist that contain far more extensive information than Wikipedia. This paper introduces a new task, called Open-Database Named-Entity Disambiguation (Open-DB NED), in which a system must be able to resolve named entities to symbols in an arbitrary database, without requiring labeled data for each new database. We introduce two techniques for Open-DB NED, one based on distant supervision and the other based on domain adaptation. In experiments on two domains, one with poor coverage by Wikipedia and the other with near-perfect coverage, our Open-DB NED strategies outperform a state-of-the-art Wikipedia NED system by over 25{\%} in accuracy.},
author = {Sil, Avirup and Cronin, Ernest and Nie, Penghai and Yang, Yinfei and Popescu, Ana-Maria and Yates, Alexander},
booktitle = {EMNLP-CoNLL 2012},
pages = {116--127},
publisher = {Association for Computational Linguistics},
title = {{Linking named entities to any database}},
url = {http://dl.acm.org/citation.cfm?id=2390948.2390963},
year = {2012}
}
@inproceedings{Karimzadehgan2011,
address = {New York, New York, USA},
author = {Karimzadehgan, Maryam and Li, Wei and Zhang, Ruofei and Mao, Jianchang},
booktitle = {Proceedings of the 20th international conference on World wide web - WWW '11},
doi = {10.1145/1963405.1963460},
file = {:Users/ikuya/papers/A stochastic learning-to-rank algorithm and its application to contextual advertising - 2011 - Karimzadehgan et al.pdf:pdf},
isbn = {9781450306324},
month = {mar},
pages = {377},
publisher = {ACM Press},
title = {{A stochastic learning-to-rank algorithm and its application to contextual advertising}},
url = {http://dl.acm.org/citation.cfm?id=1963405.1963460},
year = {2011}
}
@inproceedings{Sen2012,
address = {New York, New York, USA},
author = {Sen, Prithviraj},
booktitle = {Proceedings of the 21st international conference on World Wide Web - WWW '12},
doi = {10.1145/2187836.2187935},
isbn = {9781450312295},
keywords = {entity disambiguation,topic models},
month = {apr},
pages = {729},
publisher = {ACM Press},
title = {{Collective context-aware topic models for entity disambiguation}},
url = {http://dl.acm.org/citation.cfm?id=2187836.2187935},
year = {2012}
}
@article{Grammel2008,
author = {Grammel, Lars and Storey, Margaret-anne},
file = {:Users/ikuya/papers/An end user perspective on mashup makers - 2008 - Grammel, Storey.pdf:pdf},
journal = {University of Victoria Technical Report DCS-324-IR},
title = {{An end user perspective on mashup makers}},
url = {http://lars.grammel.googlepages.com/paper{\_}mashup{\_}makers.pdf},
year = {2008}
}
@article{Gattani2013,
author = {Gattani, Abhishek and Doan, AnHai and Lamba, Digvijay S. and Garera, Nikesh and Tiwari, Mitul and Chai, Xiaoyong and Das, Sanjib and Subramaniam, Sri and Rajaraman, Anand and Harinarayan, Venky},
doi = {10.14778/2536222.2536237},
issn = {21508097},
journal = {Proceedings of the VLDB Endowment},
month = {aug},
number = {11},
pages = {1126--1137},
publisher = {VLDB Endowment},
title = {{Entity extraction, linking, classification, and tagging for social media}},
url = {http://dl.acm.org/citation.cfm?id=2536222.2536237},
volume = {6},
year = {2013}
}
@article{Wang2010,
author = {Wang, Xiangzhi and Liu, Chunyang and Xue, Guirong and Yu, Yong},
file = {:Users/ikuya/papers/Click prediction for product search on C2C web sites - 2010 - Wang et al.pdf:pdf},
journal = {Advanced Data Mining and Applications},
keywords = {c2c,click prediction,ecommerce,logistic regression},
pages = {387--398},
title = {{Click prediction for product search on C2C web sites}},
url = {http://link.springer.com/chapter/10.1007/978-3-642-17313-4{\_}38},
year = {2010}
}
@inproceedings{Irmak2009a,
author = {Irmak, Utku and von Brzeski, Vadim and Kraft, Reiner},
booktitle = {2009 IEEE 25th International Conference on Data Engineering},
doi = {10.1109/ICDE.2009.76},
isbn = {978-1-4244-3422-0},
issn = {1084-4627},
month = {mar},
pages = {457--468},
publisher = {IEEE},
title = {{Contextual Ranking of Keywords Using Click Data}},
url = {http://dl.acm.org/citation.cfm?id=1546683.1547447},
year = {2009}
}
@inproceedings{Ostuni2013,
address = {New York, New York, USA},
author = {Ostuni, Vito Claudio and {Di Noia}, Tommaso and {Di Sciascio}, Eugenio and Mirizzi, Roberto},
booktitle = {Proceedings of the 7th ACM conference on Recommender systems - RecSys '13},
doi = {10.1145/2507157.2507172},
file = {:Users/ikuya/papers/Top-N recommendations from implicit feedback leveraging linked open data - 2013 - Ostuni et al.pdf:pdf},
isbn = {9781450324090},
month = {oct},
pages = {85--92},
publisher = {ACM Press},
title = {{Top-N recommendations from implicit feedback leveraging linked open data}},
url = {http://dl.acm.org/citation.cfm?id=2507157.2507172},
year = {2013}
}
@inproceedings{Dalvi2009,
address = {New York, New York, USA},
author = {Dalvi, Nilesh and Kumar, Ravi and Pang, Bo and Ramakrishnan, Raghu and Tomkins, Andrew and Bohannon, Philip and Keerthi, Sathiya and Merugu, Srujana},
booktitle = {Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems - PODS '09},
doi = {10.1145/1559795.1559797},
file = {:Users/ikuya/papers/A web of concepts - 2009 - Dalvi et al.pdf:pdf},
isbn = {9781605585536},
keywords = {concepts,extraction,ranking,selection},
month = {jun},
pages = {1},
publisher = {ACM Press},
title = {{A web of concepts}},
url = {http://dl.acm.org/citation.cfm?id=1559795.1559797},
year = {2009}
}
@article{Auer2009,
author = {Auer, S and Doehring, R and Dietzold, S},
file = {:Users/ikuya/papers/LESS-Template-Based Syndication and Presentation of Linked Data - 2009 - Auer, Doehring, Dietzold.pdf:pdf},
journal = {informatik.uni-leipzig.de},
title = {{LESS-Template-Based Syndication and Presentation of Linked Data}},
url = {http://www.informatik.uni-leipzig.de/{~}auer/publication/semtem.pdf},
year = {2009}
}
@inproceedings{Dill2003,
author = {Dill, Stephen and Eiron, Nadav and Gibson, David and Gruhl, Daniel and Guha, R. and Jhingran, Anant and Kanungo, Tapas and Rajagopalan, Sridhar and Tomkins, Andrew and Tomlin, John A. and Zien, Jason Y.},
booktitle = {Proceedings of the Twelfth International Conference on World Wide Web (WWW '03)},
doi = {10.1145/775152.775178},
file = {:Users/ikuya/papers/SemTag and seeker bootstrapping the semantic web via automated semantic annotation - 2003 - Dill et al.pdf:pdf},
isbn = {1581136803},
keywords = {automated semantic tagging,data mining,information retrieval,large text datasets,text analytics},
pages = {178--186},
title = {{SemTag and seeker: bootstrapping the semantic web via automated semantic annotation}},
url = {http://dl.acm.org/citation.cfm?id=775152.775178},
year = {2003}
}
@article{Rajaraman2009,
author = {Rajaraman, Anand},
file = {:Users/ikuya/papers/Kosmix Exploring the Deep Web using Taxonomies and Categorization - 2009 - Rajaraman.pdf:pdf},
journal = {IEEE Data Engineering Bulletin},
pages = {1--8},
publisher = {Citeseer},
title = {{Kosmix: Exploring the Deep Web using Taxonomies and Categorization}},
url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.152.8111{\&}amp;rep=rep1{\&}amp;type=pdf},
year = {2009}
}
@inproceedings{Han2008a,
address = {Yorktown Heights, New York, USA},
author = {Han, Hao and Tokuda, Takehiro},
booktitle = {Proceedings of the 2008 Eighth International Conference on Web Engineering},
doi = {10.1109/ICWE.2008.29},
file = {:Users/ikuya/papers/A Method for Integration of Web Applications Based on Information Extraction - 2008 - Han, Tokuda.pdf:pdf},
keywords = {end-user programming,information ex-,mashup,traction,web application integration,web service},
month = {jul},
pages = {189--195},
publisher = {IEEE Computer Society},
title = {{A Method for Integration of Web Applications Based on Information Extraction}},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4577882},
year = {2008}
}
@article{Malecha2010,
author = {Malecha, Gregory and Smith, Ian},
file = {:Users/ikuya/papers/Maximum Entropy Part-of-Speech Tagging in NLTK Implementing the Maximum Entropy Tagger - 2010 - Malecha, Smith.pdf:pdf},
journal = {Interface},
pages = {1--10},
title = {{Maximum Entropy Part-of-Speech Tagging in NLTK Implementing the Maximum Entropy Tagger}},
year = {2010}
}
@inproceedings{Milne2008,
abstract = {This paper describes how to automatically cross-reference documents with Wikipedia: the largest knowledge base ever known. It explains how machine learning can be used to identify significant terms within unstructured text, and enrich it with links to the appropriate Wikipedia articles. The resulting link detector and disambiguator performs very well, with recall and precision of almost 75{\%}. This performance is constant whether the system is evaluated on Wikipedia articles or "real world" documents. This work has implications far beyond enriching documents with explanatory links. It can provide structured knowledge about any unstructured fragment of text. Any task that is currently addressed with bags of words - indexing, clustering, retrieval, and summarization to name a few - could use the techniques described here to draw on a vast network of concepts and semantics.},
annote = {- Wikipedia内のリンクを学習データとして利用
- Commonness {\&}amp; Relatedness
- Commonness: 対象記事にリンクが張られる事前確率
- Relatedness: コンテクストとの類似度

- 記事同士の関連度をIncoming linksとexternal linksの類似度で計測
- Context自体の質の良さをコンテクストの総和で判定

- まれなキーワードは無視},
author = {Milne, David and Witten, Ian H.},
booktitle = {Proceeding of the 17th ACM Conference on Information and Knowledge Management (CIKM)},
doi = {10.1145/1458082.1458150},
file = {:Users/ikuya/papers/Learning to Link with Wikipedia - 2008 - Milne, Witten.pdf:pdf},
isbn = {9781595939913},
keywords = {data mining,semantic annotation,wikipedia,word sense,word sense disambiguation},
pages = {509--518},
title = {{Learning to Link with Wikipedia}},
year = {2008}
}
@article{Irmak2010,
author = {Irmak, Utku and Kraft, R},
file = {:Users/ikuya/papers/A scalable machine-learning approach for semi-structured named entity recognition - 2010 - Irmak, Kraft.pdf:pdf},
journal = {19th international conference on World wide web},
keywords = {boostrapping algorithm,ner,weakly-supervised learning},
title = {{A scalable machine-learning approach for semi-structured named entity recognition}},
url = {http://portal.acm.org/citation.cfm?id=1772738},
year = {2010}
}
@inproceedings{Abiteboul2009,
author = {Abiteboul, S and Greenshpan, O and Milo, T and Polyzotis, N},
booktitle = {Proceedings of the 2009 IEEE International Conference on Data Engineering},
file = {:Users/ikuya/papers/Matchup Autocompletion for mashups - 2009 - Abiteboul et al.pdf:pdf},
pages = {1479--1482},
publisher = {IEEE Computer Society},
title = {{Matchup: Autocompletion for mashups}},
url = {http://users.soe.ucsc.edu/{~}alkis/papers/matchup.pdf},
volume = {09},
year = {2009}
}
@inproceedings{lu-roth:2015:EMNLP,
address = {Lisbon},
author = {Lu, Wei and Roth, Dan},
booktitle = {Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing},
pages = {857--867},
publisher = {Association for Computational Linguistics},
title = {{Joint Mention Extraction and Classification with Mention Hypergraphs}},
url = {http://aclweb.org/anthology/D15-1102},
year = {2015}
}
@article{chang2014e2e,
author = {Chang, Ming-Wei and Hsu, Bo-June and Ma, Hao and Loynd, Ricky and Wang, Kuansan},
journal = {4th Workshop on Making Sense of Microposts ({\#}Microposts2014)},
pages = {62--63},
title = {{E2E: An End-to-End Entity Linking System for Short and Noisy Text}},
year = {2014}
}
@inproceedings{MENDES12.570,
address = {Istanbul, Turkey},
author = {Mendes, Pablo and Jakob, Max and Bizer, Christian},
booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
editor = {Chair), Nicoletta Calzolari (Conference and Choukri, Khalid and Declerck, Thierry and Doğan, Mehmet Uğur and Maegaard, Bente and Mariani, Joseph and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios},
isbn = {978-2-9517408-7-7},
publisher = {European Language Resources Association (ELRA)},
title = {{DBpedia: A Multilingual Cross-domain Knowledge Base}},
year = {2012}
}
@inproceedings{Zheng2012,
abstract = {Entity disambiguation with a knowledge base becomes increasingly popular in the NLP community. In this paper, we employ Freebase as the knowledge base, which contains significantly more entities than Wikipedia and others. While huge in size, Freebase lacks context for most entities, such as the descriptive text and hyperlinks in Wikipedia, which are useful for disambiguation. Instead, we leverage two features of Freebase, namely the naturally disambiguated mention phrases (aka aliases) and the rich taxonomy, to perform disambiguation in an iterative manner. Specifically, we explore both generative and discriminative models for each iteration. Experiments on 2, 430, 707 English sentences and 33, 743 Freebase entities show the effectiveness of the two features, where 90{\%} accuracy can be reached without any labeled data. We also show that discriminative models with proposed split training strategy is robust against over fitting problem, and constantly outperforms the generative ones.},
address = {Macau, China},
annote = {FreebaseでNamed Entity Disambiguationする
Freebaseは22 million entities、Wikipediaは3.9 million entities
Wikipediaよりも良いType taxonomyと複雑なスキーマ},
author = {Zheng, Zhicheng and Si, Xiance and Li, Fangtao and Chang, EY and Zhu, Xiaoyan},
booktitle = {Proceedings of the 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology},
file = {:Users/ikuya/papers/Entity Disambiguation with Freebase - 2012 - Zheng et al.pdf:pdf},
keywords = {-freebase,disambiguated,freebase,name entity disambiguation,named entity disambiguation,named entity linking,naturally,type taxonomy},
mendeley-tags = {freebase,named entity disambiguation,named entity linking},
pages = {82--89},
title = {{Entity Disambiguation with Freebase}},
url = {http://dl.acm.org/citation.cfm?id=2457667},
year = {2012}
}
@inproceedings{Simmen2008a,
abstract = {Increasingly large numbers of situational applications are being created by enterprise business users as a by-product of solving day-to-day problems. In efforts to address the demand for such applications, corporate IT is moving toward Web 2.0 architectures. In particular, the corporate intranet is evolving into a platform of readily accessible data and services where communities of business users can assemble and deploy situational applications. Damia is a web style data integration platform being developed to address the data problem presented by such applications, which often access and combine data from a variety of sources. Damia allows business users to quickly and easily create data mashups that combine data from desktop, web, and traditional IT sources into feeds that can be consumed by AJAX, and other types of web applications. This paper describes the key features and design of Damia's data integration engine, which has been packaged with Mashup Hub, an enterprise feed server currently available for download on IBM alphaWorks. Mashup Hub exposes Damia's data integration capabilities in the form of a service that allows users to create hosted data mashups.},
address = {Vancouver, Canada},
author = {Simmen, David E. and Altinel, Mehmet and Markl, Volker and Padmanabhan, Sriram and Singh, Ashutosh},
booktitle = {Proceedings of the 2008 ACM SIGMOD international conference on Management of data},
file = {:Users/ikuya/papers//Damia data mashups for intranet applications - 2008 - Simmen et al.pdf:pdf},
keywords = {data feeds,information integration,xml},
pages = {171--1182},
publisher = {ACM},
title = {{Damia: data mashups for intranet applications}},
url = {http://portal.acm.org/citation.cfm?id=1376616.1376734},
year = {2008}
}
@inproceedings{okazaki-EtAl:2008:EMNLP,
address = {Honolulu},
author = {Okazaki, Naoaki and Tsuruoka, Yoshimasa and Ananiadou, Sophia and Tsujii, Jun'ichi},
booktitle = {Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing},
pages = {447--456},
publisher = {Association for Computational Linguistics},
title = {{A Discriminative Candidate Generator for String Transformations}},
url = {http://www.aclweb.org/anthology/D08-1047},
year = {2008}
}
@inproceedings{Bollacker2008,
author = {Bollacker, Kurt and Evans, Colin and Paritosh, Praveen and Sturge, Tim and Taylor, Jamie},
booktitle = {Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data (SIGMOD '08)},
doi = {10.1145/1376616.1376746},
isbn = {9781605581026},
keywords = {collaborative systems,semantic network,tuple store},
pages = {1247--1250},
title = {{Freebase: a collaboratively created graph database for structuring human knowledge}},
url = {http://dl.acm.org/citation.cfm?id=1376616.1376746},
year = {2008}
}
@inproceedings{Le-Phuoc2009,
abstract = {The use of RDF data published on the Web for applications is still a cumbersome and resource-intensive task due to the limited software support and the lack of standard programming paradigms to deal with everyday problems such as combination of RDF data from dierent sources, object identifier consolidation, ontology alignment and mediation, or plain querying and filtering tasks. In this paper we present a framework, Semantic Web Pipes, that supports fast implementation of Semantic data mash-ups while preserving desirable properties such as abstraction, encapsulation, component-orientation, code re-usability and maintainability which are common and well supported in other application areas.},
author = {Le-Phuoc, Danh and Polleres, Axel and Hauswirth, Manfred and Tummarello, Giovanni and Morbidoni, Christian},
booktitle = {Proceedings of the 18th international conference on World wide web},
file = {:Users/ikuya/papers/Rapid prototyping of semantic mash-ups through semantic web pipes - 2009 - Le-Phuoc et al.pdf:pdf},
keywords = {DERI pipes,RDF,linked data,mash-up,mashup editors,mashups,pipes,semantic web},
mendeley-tags = {DERI pipes,linked data,mashup editors,mashups,semantic web},
title = {{Rapid prototyping of semantic mash-ups through semantic web pipes}},
url = {http://portal.acm.org/citation.cfm?id=1526788},
year = {2009}
}
@inproceedings{Lehmann2010,
author = {Lehmann, John and Monahan, Sean and Nezda, Luke and Jung, Arnold and Shi, Ying},
booktitle = {Proceeding of Text Analytics Conference (TAC)},
title = {{LCC Approaches to Knowledge Base Population at TAC 2010}},
url = {http://www.nist.gov/tac/publications/2010/participant.papers/lcc.proceedings.pdf},
year = {2010}
}
@inproceedings{Bouillet2009,
author = {Bouillet, Eric and Feblowitz, Mark and Feng, H. and Ranganathan, Anand and Riabov, A. and Udrea, Octavian and Liu, Z.},
booktitle = {Proceedings of the 10th ACM/IFIP/USENIX International Conference on Middleware},
file = {:Users/ikuya/papers/MARIO middleware for assembly and deployment of multi-platform flow-based applications - 2009 - Bouillet et al.pdf:pdf},
pages = {1--7},
publisher = {Springer-Verlag New York, Inc.},
title = {{MARIO: middleware for assembly and deployment of multi-platform flow-based applications}},
url = {http://portal.acm.org/citation.cfm?id=1656980.1657015},
year = {2009}
}
@inproceedings{Han2009,
author = {Han, Xianpei and Zhao, Jun},
booktitle = {Proceeding of the 18th ACM conference on Information and knowledge management - CIKM '09},
doi = {10.1145/1645953.1645983},
file = {:Users/ikuya/papers/Named entity disambiguation by leveraging wikipedia semantic knowledge - 2009 - Han, Zhao.pdf:pdf},
isbn = {9781605585123},
keywords = {coreference resolution,name ambiguity,named entity disambiguation,record linkage,semantic knowledge},
month = {nov},
pages = {215},
publisher = {ACM Press},
title = {{Named entity disambiguation by leveraging wikipedia semantic knowledge}},
url = {http://dl.acm.org/citation.cfm?id=1645953.1645983},
year = {2009}
}
@article{CopicPucihar2013,
address = {New York, New York, USA},
author = {{{\v{C}}opi{\v{c}} Pucihar}, Klen and Coulton, Paul and Alexander, Jason},
doi = {10.1145/2493190.2494660},
file = {:Users/ikuya/papers/Creating a stereoscopic magic-lens to improve depth perception in handheld augmented reality - 2013 - {\v{C}}opi{\v{c}} Pucihar, Coulton, Alexande.pdf:pdf},
isbn = {9781450322737},
journal = {Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services - MobileHCI '13},
pages = {448},
publisher = {ACM Press},
title = {{Creating a stereoscopic magic-lens to improve depth perception in handheld augmented reality}},
url = {http://dl.acm.org/citation.cfm?doid=2493190.2494660},
year = {2013}
}
@inproceedings{Hassan2011,
abstract = {This paper introduces a novel method for measuring semantic relatedness using semantic profiles constructed from salient encyclopedic features. The model is built on the notion that the meaning of a word can be characterized by the salient concepts found in its immediate context. In addition to being computationally efficient, the new model has superior performance and remarkable consistency when compared to both knowledge-based and corpus-based state-of-the-art semantic relatedness models.},
author = {Hassan, Samer and Mihalcea, Rada},
booktitle = {Proceedings of the 25th AAAI Conference on Artificial Intelligence, (AAAI 2011)},
file = {:Users/ikuya/papers/Semantic Relatedness Using Salient Semantic Analysis. - 2011 - Hassan, Mihalcea.pdf:pdf},
pages = {884--889},
title = {{Semantic Relatedness Using Salient Semantic Analysis.}},
url = {http://www.samerhassan.com/images/4/48/Hassan.pdf$\backslash$nhttp://www.aaai.org/ocs/index.php/AAAI/AAAI11/paper/download/3616/3972},
year = {2011}
}
@inproceedings{Paulheim2013,
author = {Paulheim, H and Bizer, C},
booktitle = {The Semantic Web–ISWC 2013},
file = {:Users/ikuya/papers/Type inference on noisy rdf data - 2013 - Paulheim, Bizer.pdf:pdf},
title = {{Type inference on noisy rdf data}},
url = {http://www.heikopaulheim.com/docs/iswc2013.pdf http://link.springer.com/chapter/10.1007/978-3-642-41335-3{\_}32},
year = {2013}
}
@article{YipingZhou,
author = {{Yiping Zhou}, Lan Nie, Omid Rouhani-kalleh, Flavian Vasile, Scott Gaffney},
file = {:Users/ikuya/papers/Resolving Surface Forms to Wikipedia Topics - 2010 - Zhou et al.pdf:pdf},
title = {{Resolving surface forms to wikipedia topics}},
url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.231.6411}
}
@article{Cornolti2013,
author = {Cornolti, Marco and Ferragina, Paolo and Ciaramita, Massimiliano},
file = {:Users/ikuya/papers/A framework for benchmarking entity-annotation systems - 2013 - Cornolti, Ferragina, Ciaramita.pdf:pdf},
isbn = {978-1-4503-2035-1},
keywords = {wikipedia},
month = {may},
pages = {249--260},
publisher = {International World Wide Web Conferences Steering Committee},
title = {{A framework for benchmarking entity-annotation systems}},
url = {http://dl.acm.org/citation.cfm?id=2488388.2488411},
year = {2013}
}
@article{Daniel2009b,
author = {Daniel, Florian and Casati, Fabio and Benatallah, Boualem and Shan, M.C.},
file = {:Users/ikuya/papers/Hosted Universal Composition Models, Languages and Infrastructure in mashArt - 2009 - Daniel et al.pdf:pdf},
journal = {Conceptual Modeling-ER 2009},
pages = {428--443},
publisher = {Springer},
title = {{Hosted Universal Composition: Models, Languages and Infrastructure in mashArt}},
url = {http://www.springerlink.com/index/JKHK212034516723.pdf},
year = {2009}
}
@article{Iacobelli2010,
author = {Iacobelli, Francisco and Hammond, Kristian and Birnbaum, Larry},
file = {:Users/ikuya/papers/Synergy Between Automatic Content Generation and Social Media - 2010 - Iacobelli, Hammond, Birnbaum.pdf:pdf},
journal = {Information Retrieval},
title = {{Synergy Between Automatic Content Generation and Social Media}},
year = {2010}
}
@inproceedings{Roth2009,
address = {New York, New York, USA},
author = {Roth, Volker and Turner, Thea},
booktitle = {Proceedings of the 27th international conference on Human factors in computing systems - CHI 09},
doi = {10.1145/1518701.1518933},
file = {:Users/ikuya/papers/Bezel swipe - 2009 - Roth, Turner.pdf:pdf},
isbn = {9781605582467},
keywords = {crossing,cut paste,gesture,handheld,iphone,mobile device,mode change,multiple selection,small display,study,swipe,touch interaction,zoomable,zooming},
month = {apr},
pages = {1523},
publisher = {ACM Press},
title = {{Bezel swipe}},
url = {http://dl.acm.org/citation.cfm?id=1518701.1518933},
year = {2009}
}
@inproceedings{Ferragina2010,
author = {Ferragina, Paolo and Scaiella, Ugo},
booktitle = {Proceedings of the 19th ACM International Conference on Information and Knowledge Management (CIKM)},
file = {:Users/ikuya/papers/TAGME On-the-fly Annotation of Short Text Fragments (by Wikipedia Entities) - 2010 - Ferragina, Scaiella(3).pdf:pdf;:Users/ikuya/papers/TAGME On-the-fly Annotation of Short Text Fragments (by Wikipedia Entities) - 2010 - Ferragina, Scaiella(2).pdf:pdf},
isbn = {9781450300995},
pages = {1625--1628},
title = {{TAGME: On-the-fly Annotation of Short Text Fragments (by Wikipedia Entities)}},
url = {http://dl.acm.org/citation.cfm?id=1871689},
year = {2010}
}
@inproceedings{hu-EtAl:2015:ACL-IJCNLP,
author = {Hu, Zhiting and Huang, Poyao and Deng, Yuntian and Gao, Yingkai and Xing, Eric},
booktitle = {Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (ACL-IJCNLP) (Volume 1: Long Papers)},
pages = {1292--1300},
title = {{Entity Hierarchy Embedding}},
url = {http://www.aclweb.org/anthology/P15-1125},
year = {2015}
}
@article{Hu2009,
address = {New York, New York, USA},
author = {Hu, Jian and Wang, Gang and Lochovsky, Fred and Sun, Jian-tao and Chen, Zheng},
doi = {10.1145/1526709.1526773},
file = {:Users/ikuya/papers/Understanding user's query intent with wikipedia - 2009 - Hu et al.pdf:pdf},
isbn = {9781605584874},
journal = {Proceedings of the 18th international conference on World wide web - WWW '09},
pages = {471},
publisher = {ACM Press},
title = {{Understanding user's query intent with wikipedia}},
url = {http://portal.acm.org/citation.cfm?doid=1526709.1526773},
year = {2009}
}
@inproceedings{Gale1992,
address = {Morristown, NJ, USA},
author = {Gale, William A. and Church, Kenneth W. and Yarowsky, David},
booktitle = {Proceedings of the workshop on Speech and Natural Language - HLT '91},
doi = {10.3115/1075527.1075579},
file = {:Users/ikuya/papers/One sense per discourse - 1992 - Gale, Church, Yarowsky.pdf:pdf},
isbn = {1558602720},
month = {feb},
pages = {233},
publisher = {Association for Computational Linguistics},
title = {{One sense per discourse}},
url = {http://dl.acm.org/citation.cfm?id=1075527.1075579},
year = {1992}
}
@article{Sha2003,
author = {Sha, Fei},
file = {:Users/ikuya/papers/Shallow parsing with conditional random fields - 2003 - Sha.pdf:pdf},
journal = {Proceedings of the 2003 Conference of the North},
number = {June},
pages = {134--141},
title = {{Shallow parsing with conditional random fields}},
url = {http://dl.acm.org/citation.cfm?id=1073473},
year = {2003}
}
@article{Nothman2009,
author = {Nothman, Joel and Murphy, Tara and Curran, James R},
file = {:Users/ikuya/papers/Analysing Wikipedia and Gold-Standard Corpora for NER Training - 2009 - Nothman, Murphy, Curran.pdf:pdf},
number = {April},
pages = {612--620},
title = {{Analysing Wikipedia and Gold-Standard Corpora for NER Training}},
year = {2009}
}
@article{Rubenstein1965,
abstract = {Experimental corroboration was obtained for the hypothesis that the proportion of words common to the contexts of word A and to the contexts of word B is a function of the degree to which A and B are similar in meaning. The tests were carried out for variously defined contexts. The shapes of the functions, however, indicate that similarity of context is reliable as criterion only for detecting pairs of words that are very similar in meaning.},
author = {Rubenstein, Herbert and Goodenough, John B.},
journal = {Communications of the ACM},
number = {10},
pages = {627--633},
title = {{Contextual Correlates of Synonymy}},
volume = {8},
year = {1965}
}
@article{Csomai2008,
author = {Csomai, Andras and Mihalcea, Rada},
file = {:Users/ikuya/papers/Linking documents to encyclopedic knowledge - 2008 - Csomai, Mihalcea.pdf:pdf},
journal = {Intelligent Systems, IEEE},
keywords = {annotates web pages following,as wikify,extraction and word-sense disambigua-,functions into a sys-,s guide-,tem,that automatically,tion,we combine these two,which we refer to,wikipedia},
number = {5},
pages = {34--41},
title = {{Linking documents to encyclopedic knowledge}},
url = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=4629724},
volume = {23},
year = {2008}
}
@article{TACL494,
abstract = {Entity disambiguation with Wikipedia relies on structured
information from redirect pages, article text, inter-article links, and
categories. We explore whether web links can replace a curated
encyclopaedia, obtaining entity prior, name, context, and coherence models
from a corpus of web pages with links to Wikipedia. Experiments compare web
link models to Wikipedia models on well-known CoNLL and TAC data sets.
Results show that using 34 million web links approaches Wikipedia
performance. Combining web link and Wikipedia models produces the best-known
disambiguation accuracy of 88.7 on standard newswire test data.},
author = {Chisholm, Andrew  and Hachey, Ben},
issn = {2307-387X},
journal = {Transactions of the Association for Computational Linguistics},
pages = {145--156},
title = {{Entity Disambiguation with Web Links}},
url = {https://tacl2013.cs.columbia.edu/ojs/index.php/tacl/article/view/494},
volume = {3},
year = {2015}
}
@article{Wang2014,
author = {Wang, Ziqi and Xu, Gu and Li, Hang and Zhang, Ming},
doi = {10.1109/TKDE.2013.11},
issn = {1041-4347},
journal = {IEEE Transactions on Knowledge and Data Engineering},
keywords = {Accuracy,Computing Methodologies,Data mining,Dictionaries,Document and Text Editing,Document and Text Processing,Error correction,Indexes,Information Search and Retrieval,Information Storage and Retrieval,Information Technology and Systems,Log Linear Model,Probabilistic logic,Query formulation,Spelling,String Transformation,String transformation,Training data,Web search queries,bioinformatics,conditional probability distribution,data mining,information retrieval,input string,learning (artificial intelligence),learning method,log linear model,maximum likelihood estimation,natural language processing,output strings,parameter estimation,probabilistic approach,probability,query processing,query reformulation,spelling error correction,string generation algorithm,string transformation},
language = {English},
month = {may},
number = {5},
pages = {1063--1075},
publisher = {IEEE},
title = {{A Probabilistic Approach to String Transformation}},
url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=6412665},
volume = {26},
year = {2014}
}
@article{Bigham,
author = {Bigham, Jeffrey P and Kaminsky, Ryan S and Nichols, Jeffrey and Jose, San},
file = {:Users/ikuya/papers/Mining Web Interactions to Automatically Create Mash-Ups - Unknown - Bigham et al.pdf:pdf},
journal = {Library},
keywords = {deep web,mash-ups,meta-,programming-by-example,search,web forms},
title = {{Mining Web Interactions to Automatically Create Mash-Ups}}
}
@article{Fedosov2013,
author = {Fedosov, Anton},
file = {:Users/ikuya/papers/Mobile Augmented Reality Exploring Content in Natural and Controlled Settings Using 3D Tracking - 2013 - Fedosov.pdf:pdf},
isbn = {9781450322737},
pages = {460--463},
title = {{Mobile Augmented Reality : Exploring Content in Natural and Controlled Settings Using 3D Tracking}},
year = {2013}
}
@article{Ikeda2008,
address = {New York, New York, USA},
author = {Ikeda, Sohei and Nagamine, Takakazu and Kamada, Tomio},
doi = {10.1145/1497308.1497319},
file = {:Users/ikuya/papers/Application framework with demand-driven mashup for selective browsing - 2008 - Ikeda, Nagamine, Kamada.pdf:pdf},
isbn = {9781605583495},
journal = {Proceedings of the 10th International Conference on Information Integration and Web-based Applications {\&} Services - iiWAS '08},
number = {10},
pages = {33},
publisher = {ACM Press},
title = {{Application framework with demand-driven mashup for selective browsing}},
url = {http://portal.acm.org/citation.cfm?doid=1497308.1497319},
volume = {15},
year = {2008}
}
@article{Attarwala2013,
address = {New York, New York, USA},
author = {Attarwala, Abbas and Munteanu, Cosmin and Baecker, Ronald},
doi = {10.1145/2493190.2494658},
file = {:Users/ikuya/papers/An accessible, large-print, listening and talking e-book to support families reading together - 2013 - Attarwala, Munteanu, Baecker.pdf:pdf},
isbn = {9781450322737},
journal = {Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services - MobileHCI '13},
keywords = {Copyright 2013 University of Toronto},
pages = {440},
publisher = {ACM Press},
title = {{An accessible, large-print, listening and talking e-book to support families reading together}},
url = {http://dl.acm.org/citation.cfm?doid=2493190.2494658},
year = {2013}
}
@inproceedings{StefanPietschmann2009,
author = {StefanPietschmann, M.V. and Rumpel, A. and Mei{\ss}ner, Klaus},
booktitle = {Web Engineering: 9th International Conference, ICWE 2009 San Sebasti{\'{a}}n, Spain, June 24-26 2009 Proceedings},
file = {:Users/ikuya/papers/CRUISe Composition of Rich User Interface Services - 2009 - StefanPietschmann, Rumpel, Mei{\ss}ner.pdf:pdf},
pages = {473},
publisher = {Springer-Verlag New York Inc},
title = {{CRUISe: Composition of Rich User Interface Services}},
url = {http://books.google.com/books?hl=en{\&}amp;lr={\&}amp;id=4MQ5qWYDI7wC{\&}amp;oi=fnd{\&}amp;pg=PA473{\&}amp;dq=CRUISe:+Composition+of+Rich+User+Interface+Services{\&}amp;ots=doWyUj3CpZ{\&}amp;sig=cDmog5rMLqpifoLzwq55IDmYZhk},
year = {2009}
}
@article{Pantel2009,
author = {Pantel, Patrick and Crestan, Eric and Borkovsky, Arkady and Popescu, Ana-Maria and Vyas, Vishnu},
file = {:Users/ikuya/papers/Web-scale distributional similarity and entity set expansion - 2009 - Pantel et al.pdf:pdf},
isbn = {978-1-932432-62-6},
month = {aug},
pages = {938--947},
publisher = {Association for Computational Linguistics},
title = {{Web-scale distributional similarity and entity set expansion}},
url = {http://dl.acm.org/citation.cfm?id=1699571.1699635},
year = {2009}
}
@article{MoiraRegelson,
author = {Regelson, M and Fain, D},
file = {:Users/ikuya/papers/Predicting click-through rate using keyword clusters - 2006 - Regelson, Fain.pdf:pdf},
journal = {Proceedings of the Second Workshop on Sponsored {\ldots}},
title = {{Predicting click-through rate using keyword clusters}},
url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.130.9999 http://diyhpl.us/{~}bryan/papers2/marketing/Predicting click-through rate using keyword clusters.pdf},
year = {2006}
}
@inproceedings{McNamee2009,
author = {McNamee, P and Dang, HT},
booktitle = {Proceeding of Text Analysis Conference (TAC)},
file = {:Users/ikuya/papers/Overview of the TAC 2009 Knowledge Base Population Track - 2009 - McNamee, Dang.pdf:pdf},
title = {{Overview of the TAC 2009 Knowledge Base Population Track}},
year = {2009}
}
@article{Rajaraman2009a,
author = {Rajaraman, Anand},
file = {:Users/ikuya/papers/Kosmix high-performance topic exploration using the deep web - 2009 - Rajaraman.pdf:pdf},
journal = {Proceedings of the VLDB Endowment},
number = {2},
pages = {1524--1529},
publisher = {VLDB Endowment},
title = {{Kosmix: high-performance topic exploration using the deep web}},
url = {http://portal.acm.org/citation.cfm?id=1687553.1687581},
volume = {2},
year = {2009}
}
@article{Hachey2012,
author = {Hachey, Ben and Radford, Will and Nothman, Joel and Honnibal, Matthew and Curran, James R.},
doi = {10.1016/j.artint.2012.04.005},
file = {:Users/ikuya/papers/Evaluating entity linking with Wikipedia - 2012 - Hachey et al.pdf:pdf},
issn = {00043702},
journal = {Artificial Intelligence},
keywords = {named entity linking},
pages = {130--150},
publisher = {Elsevier B.V.},
title = {{Evaluating entity linking with Wikipedia}},
volume = {194},
year = {2012}
}
@inproceedings{pershina-he-grishman:2015:NAACL-HLT,
author = {Pershina, Maria and He, Yifan and Grishman, Ralph},
booktitle = {Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)},
pages = {238--243},
title = {{Personalized Page Rank for Named Entity Disambiguation}},
url = {http://www.aclweb.org/anthology/N15-1026},
year = {2015}
}
@article{Finkel2007,
author = {Finkel, Jenny Rose and British, Conll-},
file = {:Users/ikuya/papers/Named Entity Recognition and the Stanford NER Software - 2007 - Finkel, British.pdf:pdf},
journal = {Organization},
pages = {1--4},
title = {{Named Entity Recognition and the Stanford NER Software}},
year = {2007}
}
@inproceedings{NIPS2013_5028,
author = {Socher, Richard and Chen, Danqi and Manning, Christopher D and Ng, Andrew},
booktitle = {Advances in Neural Information Processing Systems (NIPS)},
pages = {926--934},
title = {{Reasoning With Neural Tensor Networks for Knowledge Base Completion}},
url = {http://papers.nips.cc/paper/5028-reasoning-with-neural-tensor-networks-for-knowledge-base-completion.pdf},
year = {2013}
}
@article{Grineva2009,
author = {Grineva, Maria and Grinev, Maxim and Lizorkin, D},
file = {:Users/ikuya/papers/Extracting key terms from noisy and multitheme documents - 2009 - Grineva, Grinev, Lizorkin.pdf:pdf},
isbn = {9781605584874},
journal = {{\ldots} of the 18th international conference on {\ldots}},
keywords = {community detection,extraction,graph analysis,keywords,semantic similarity,wikipedia},
pages = {661--670},
title = {{Extracting key terms from noisy and multitheme documents}},
url = {http://dl.acm.org/citation.cfm?id=1526798},
year = {2009}
}
@inproceedings{liu-EtAl:2015:ACL-IJCNLP,
address = {Beijing},
author = {Liu, Quan and Jiang, Hui and Wei, Si and Ling, Zhen-Hua and Hu, Yu},
booktitle = {Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},
pages = {1501--1511},
publisher = {Association for Computational Linguistics},
title = {{Learning Semantic Word Embeddings based on Ordinal Knowledge Constraints}},
url = {http://www.aclweb.org/anthology/P15-1145},
year = {2015}
}
@inproceedings{Mihalcea2007,
abstract = {This paper introduces the use of Wikipedia as a resource for automatic keyword extraction and word sense disambiguation, and shows how this online encyclopedia can be used to achieve state-of-the-art results on both these tasks. The paper also shows how the two methods can be combined into a system able to automatically enrich a text with links to encyclopedic knowledge. Given an input document, the system identifies the important concepts in the text and automatically links these concepts to the corresponding Wikipedia pages. Evaluations of the system show that the automatic annotations are reliable and hardly distinguishable from manual annotations.},
author = {Mihalcea, Rada and Csomai, Andras},
booktitle = {Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management (CIKM)},
file = {:Users/ikuya/papers/Wikify! Linking Documents to Encyclopedic Knowledge - 2007 - Mihalcea, Csomai.pdf:pdf},
isbn = {9781595938039},
keywords = {keyword extraction,wikipedia,word sense disambiguation},
pages = {233--242},
title = {{Wikify!: Linking Documents to Encyclopedic Knowledge}},
url = {http://dl.acm.org/citation.cfm?id=1321475},
year = {2007}
}
@article{Ciaramita2008,
address = {New York, New York, USA},
author = {Ciaramita, Massimiliano and Murdock, Vanessa and Plachouras, Vassilis},
doi = {10.1145/1367497.1367529},
file = {:Users/ikuya/papers/Online learning from click data for sponsored search - 2008 - Ciaramita, Murdock, Plachouras.pdf:pdf},
isbn = {9781605580852},
journal = {Proceeding of the 17th international conference on World Wide Web - WWW '08},
keywords = {online learning,perceptrons,ranking,sponsored search},
pages = {227},
publisher = {ACM Press},
title = {{Online learning from click data for sponsored search}},
url = {http://portal.acm.org/citation.cfm?doid=1367497.1367529},
year = {2008}
}
@article{Marcus1993,
author = {Marcus, Mitchell P. and Marcinkiewicz, Mary Ann and Santorini, Beatrice},
file = {:Users/ikuya/papers/Building a large annotated corpus of English the penn treebank - 1993 - Marcus, Marcinkiewicz, Santorini.pdf:pdf},
issn = {0891-2017},
journal = {Computational Linguistics},
month = {jun},
number = {2},
pages = {313--330},
publisher = {MIT Press},
title = {{Building a large annotated corpus of English: the penn treebank}},
url = {http://dl.acm.org/citation.cfm?id=972470.972475},
volume = {19},
year = {1993}
}
@article{Maraikar2008,
author = {Maraikar, Z and Lazovik, A and Arbab, F},
file = {:Users/ikuya/papers/Building Mashups for the Enterprise with SABRE - 2008 - Maraikar, Lazovik, Arbab.pdf:pdf},
journal = {Service-Oriented Computing–ICSOC 2008},
pages = {70--83},
publisher = {Springer},
title = {{Building Mashups for the Enterprise with SABRE}},
url = {http://www.springerlink.com/index/67q67l8q172141uj.pdf},
year = {2008}
}
@inproceedings{Ceccarelli2013,
author = {Ceccarelli, Diego and Lucchese, Claudio and Orlando, Salvatore and Perego, Raffaele and Trani, Salvatore},
booktitle = {Proceedings of the 22nd ACM International Conference on Information and Knowledge Management (CIKM)},
doi = {10.1145/2505515.2505711},
file = {:Users/ikuya/papers/Learning relatedness measures for entity linking - 2013 - Ceccarelli et al.pdf:pdf},
isbn = {9781450322638},
keywords = {algorithms,design,experimentation},
pages = {139--148},
title = {{Learning Relatedness Measures for Entity Linking}},
url = {http://dl.acm.org/citation.cfm?id=2505515.2505711},
year = {2013}
}
@inproceedings{StephenGuo,
author = {Guo, Stephen and Chang, Ming-Wei and Kiciman, Emre},
booktitle = {Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT '13)},
pages = {1020--1030},
title = {{To link or not to link? a study on end-to-end Tweet entity linking}},
url = {http://www.aclweb.org/anthology/N13-1122},
year = {2013}
}
@inproceedings{Wong2007,
address = {New York, New York, USA},
author = {Wong, Jeffrey and Hong, Jason I.},
booktitle = {Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '07},
doi = {10.1145/1240624.1240842},
file = {:Users/ikuya/papers/Making mashups with marmite - 2007 - Wong, Hong.pdf:pdf},
isbn = {9781595935939},
keywords = {Marmite,mashup editors,mashups},
mendeley-tags = {Marmite,mashup editors,mashups},
pages = {1435},
publisher = {ACM Press},
title = {{Making mashups with marmite}},
url = {http://portal.acm.org/citation.cfm?doid=1240624.1240842},
year = {2007}
}
@article{Derczynski2015,
abstract = {Applying natural language processing for mining and intelligent information access to tweets (a form of microblog) is a challenging, emerging research area. Unlike carefully authored news text and other longer content, tweets pose a number of new challenges, due to their short, noisy, context-dependent, and dynamic nature. Information extraction from tweets is typically performed in a pipeline, comprising consecutive stages of language identification, tokenisation, part-of-speech tagging, named entity recognition and entity disambiguation (e.g. with respect to DBpedia). In this work, we describe a new Twitter entity disambiguation dataset, and conduct an empirical analysis of named entity recognition and disambiguation, investigating how robust a number of state-of-the-art systems are on such noisy texts, what the main sources of error are, and which problems should be further investigated to improve the state of the art.},
author = {Derczynski, Leon and Maynard, Diana and Rizzo, Giuseppe and van Erp, Marieke and Gorrell, Genevieve and Troncy, Rapha{\"{e}}l and Petrak, Johann and Bontcheva, Kalina},
doi = {10.1016/j.ipm.2014.10.006},
issn = {03064573},
journal = {Information Processing {\&} Management},
keywords = {Entity disambiguation,Information extraction,Microblogs,Named entity recognition,Twitter},
number = {2},
pages = {32--49},
title = {{Analysis of named entity recognition and linking for tweets}},
url = {http://www.sciencedirect.com/science/article/pii/S0306457314001034},
volume = {51},
year = {2015}
}
@inproceedings{Lizcano2008,
address = {Linz, Austria},
author = {Lizcano, David and Soriano, Javier and Reyes, Marcos and Hierro, Juan J.},
booktitle = {Proceedings of the 10th International Conference on Information Integration and Web-based Applications {\&} Services},
doi = {10.1109/UBICOMM.2008.61},
file = {:Users/ikuya/papers/EzWebFAST Reporting on a Successful Mashup-Based Solution for Developing and Deploying Composite Applications in the Upcoming Ubiquit.pdf:pdf},
month = {sep},
number = {c},
pages = {15--24},
publisher = {ACM},
title = {{EzWeb/FAST: Reporting on a Successful Mashup-Based Solution for Developing and Deploying Composite Applications in the Upcoming Ubiquitous SOA}},
url = {http://portal.acm.org/citation.cfm?id=1497308.1497317},
year = {2008}
}
@inproceedings{Ritter2011a,
abstract = {People tweet more than 100 Million times daily, yielding a noisy, informal, but some- times informative corpus of 140-character messages that mirrors the zeitgeist in an un- precedented manner. The performance of standard NLP tools is severely degraded on tweets. This paper addresses this issue by re-building the NLP pipeline beginning with part-of-speech tagging, through chunking, to named-entity recognition. Our novel T-NER system doubles F1 score compared with the Stanford NER system. T-NER leverages the redundancy inherent in tweets to achieve this performance, using LabeledLDA to exploit Freebase dictionaries as a source of distant supervision. LabeledLDA outperforms co- training, increasing F1 by 25{\%} over ten com- mon entity types.},
author = {Ritter, Alan and Clark, Sam and Etzioni, Oren},
booktitle = {EMNLP '11},
pages = {1524--1534},
title = {{Named Entity Recognition in Tweets : An Experimental Study}},
year = {2011}
}
@article{Dembczynski2008,
author = {Dembczynski, K},
file = {:Users/ikuya/papers/Predicting ads' click-through rate with decision rules - 2008 - Dembczynski.pdf:pdf},
journal = {{\ldots} in Online Advertising},
keywords = {ctr prediction,decision rules,ensem-,on-line advertising},
title = {{Predicting ads' click-through rate with decision rules}},
url = {http://www.cs.put.poznan.pl/dweiss/research/adrules/papers/troa.pdf},
year = {2008}
}
@article{Cammarano2007,
abstract = {Both the Resource Description Framework (RDF), used in the semantic web, and Maya Viz u-forms represent data as a graph of objects connected by labeled edges. Existing systems for flexible visualization of this kind of data require manual specification of the possible visualization roles for each data attribute. When the schema is large and unfamiliar, this requirement inhibits exploratory visualization by requiring a costly up-front data integration step. To eliminate this step, we propose an automatic technique for mapping data attributes to visualization attributes. We formulate this as a schema matching problem, finding appropriate paths in the data model for each required visualization attribute in a visualization template.},
author = {Cammarano, Mike and Dong, Xin Luna and Chan, Bryan and Klingner, Jeff and Talbot, Justin and Halevey, Alon and Hanrahan, Pat},
doi = {10.1109/TVCG.2007.70527},
file = {:Users/ikuya/papers/Visualization of heterogeneous data - 2007 - Cammarano et al.pdf:pdf},
issn = {1077-2626},
journal = {IEEE transactions on visualization and computer graphics},
keywords = {linked data,mashups,semantic web,visualization},
mendeley-tags = {linked data,mashups,semantic web,visualization},
number = {6},
pages = {1200--7},
pmid = {17968065},
title = {{Visualization of heterogeneous data}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/17968065},
volume = {13},
year = {2007}
}
@inproceedings{Gamon2013,
address = {New York, New York, USA},
author = {Gamon, Michael and Yano, Tae and Song, Xinying and Apacible, Johnson and Pantel, Patrick},
booktitle = {Proceedings of the 22nd ACM international conference on Conference on information {\&} knowledge management - CIKM '13},
doi = {10.1145/2505515.2505602},
isbn = {9781450322638},
keywords = {content analysis,document aboutness,entity salience},
month = {oct},
pages = {2375--2380},
publisher = {ACM Press},
title = {{Identifying salient entities in web pages}},
url = {http://dl.acm.org/citation.cfm?id=2505515.2505602},
year = {2013}
}
@book{Manning2008,
author = {Manning, Christopher D. and Raghavan, Prabhakar and Sch{\"{u}}tze, Hinrich},
isbn = {0521865719, 9780521865715},
publisher = {Cambridge University Press},
title = {{Introduction to Information Retrieval}},
url = {http://dl.acm.org/citation.cfm?id=1394399},
year = {2008}
}
@article{Jarvelin2002,
author = {J{\"{a}}rvelin, Kalervo and Kek{\"{a}}l{\"{a}}inen, Jaana},
doi = {10.1145/582415.582418},
issn = {10468188},
journal = {ACM Transactions on Information Systems},
keywords = {Graded relevance judgments,cumulated gain},
number = {4},
pages = {422--446},
publisher = {ACM},
title = {{Cumulated gain-based evaluation of IR techniques}},
url = {http://dl.acm.org/citation.cfm?id=582415.582418},
volume = {20},
year = {2002}
}

license: MIT

license_type: permissive

branch_name: refs/heads/master

extension: bib


text:
@article{bat,
    author={Xin-She Yang},
    title={A New Metaheuristic Bat-Inspired Algorithm},
    journal={Studies in Computational Intelligence},
    pages={65-74},
    year={2010}
}

repository: herberthamaral/mestrado

repo_name: herberthamaral/mestrado

gha_language: TeX


text:
@Article{bretagne:ijprs:2018,
  author    = {Bretagne, Estelle and Dassonvalle, Pascal and Caron, Guillaume},
  title     = {Spherical target-based calibration of terrestrial laser scanner intensity. Application to colour information computation},
  journal   = {ISPRS Journal of Photogrammetry and Remote Sensing},
  year      = {2018},
  volume    = {144},
  pages     = {14--27},
  month     = {October},
  doi       = {https://doi.org/10.1016/j.isprsjprs.2018.06.014},
  url       = {https://reader.elsevier.com/reader/sd/pii/S0924271618301771?token=1134717A44BDDFA37DFA2BFD64A3E1E4190ACB7E6ACC983D68C8F7F39CBC3FCA9435E775F2115417F1E5232B181F0848},
  keywords  = {Terrestrial laser scanning, Intensity, Incidence angle, Range, sRGB},
  abstract  = {Terrestrial Laser Scanning (TLS) acquires for each scanned point its position and an intensity. Intensity of TLS is based on a measure of the electronic signal strength which is obtained by converting and amplifying the backscattered optical power of the emitted signal. In this paper, theoretical radar equation is established and particular attention is given to the necessary assumptions. A low-cost intensity calibration method is proposed that provides measurements insensitive to range and incidence angle. This process is data driven without simplifying assumption about radiometrical properties of the spherical calibration target. For the commercial device considered, the laser wavelength is 532nm. It enables us to measure green levels. Intensity is interpreted for each point of 3D clouds in terms of green level in sRGB colour space viewed under CIE standard illuminant D65. Applications are realized on a data set acquired at Amiens cathedral. There is no more shading or multi-exposure effects compared with high-resolution camera colourisation.},
  publisher = {ELSEVIER},
  address   = {RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS NETHERLANDS}
}


text:
SUMMARY = "Collection of LADSPA/LV2/VST/JACK audio plugins for high-quality processing"
HOMEPAGE = "http://www.zamaudio.com/?p=976"
LICENSE = "GPL-2.0-only"
LIC_FILES_CHKSUM = "file://COPYING;md5=b234ee4d69f5fce4486a80fdaf4a4263"

DEPENDS += " \
    virtual/libx11 \
    virtual/libgl \
    liblo \
    jack \
    ladspa-sdk \
    rubberband \
    libsamplerate0 \
    libsndfile1 \
    fftw \
"

inherit pkgconfig lv2-turtle-helper features_check pack_audio_plugins

REQUIRED_DISTRO_FEATURES = "x11"

SRC_URI = "gitsm://github.com/zamaudio/${BPN}.git;branch=master;protocol=https"
SRCREV = "e7077fcc0b7f60daa7471eae42015ffc9cba73d9"
S = "${WORKDIR}/git"
PV = "3.14"

EXTRA_OEMAKE += " \
    NOOPT=true \
    SKIP_STRIPPING=true \
"

do_install() {
    ${MAKE} DESTDIR=${D} PREFIX= LIBDIR=${libdir} BINDIR=${bindir} install
}

PACKAGES =+ "${PN}-standalone"
FILES:${PN}-standalone = "${bindir}"

repository: schnitzeltony/meta-musicians

repo_name: schnitzeltony/meta-musicians

gha_license_id: MIT

gha_language: BitBake

extension: bb


text:
@online{mannedspaceflight,
  title={Extravehicular Activity Manned Space Flight},
  url={https://www.encyclopedia.com/social-sciences-and-law/economics-business-and-labor/businesses-and-occupations/extravehicular-activity-manned-space-flight},
  author={encyclopedia},
  year={2016},
  publisher={The Gale Group}
}
@report{violajones,
  title={Rapid Object Detection using a Boosted Cascade of Simple Features},
  author={Paul Viola and Michael Jones},
  year={2001},
  publisher={ieee},
  url={https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=990517&tag=1}
}
@online{mrbasics,
  title={MR Basics 100: Getting started with Unity},
  author={microsoft},
  url={https://docs.microsoft.com/en-us/windows/mixed-reality/holograms-100},
  year={2018},
  publisher={Microsoft}
}

repository: jschmidtnj/SpaceSuits

repo_name: jschmidtnj/SpaceSuits


text:
@article{antal_ceereport_2020,
	title = {{Retrospective harmonization of survey data files in R}},
	shorttitle = {Retrospective harmonization of survey data files in R},
	language = {English},
	url = {http://retroharmonize.satellitereport.com},
	doi = {http://doi.org/10.5281/zenodo.3937746},
	author = {Antal, Daniel},
	publisher = {{satellitereport.com}},
	year = {2020}
}

repository: antaldaniel/private-website

repo_name: antaldaniel/private-website


text:
@online{noauthor_blue_nodate,
	title = {Blue {KC} Expands Grant Funding with {KCALSI} Kansas City Area Life Sciences Institute},
	url = {http://www.kclifesciences.org/news/life-sciences-bulletin/2013-life-sciences-bulletin/blue-kc-expands-grant-funding-with-kcalsi/},
	urldate = {2013-06-27}
}

repository: pmean/build-website

repo_name: pmean/build-website


text:
DESCRIPTION = "Skins for Enigma2"
MAINTAINER = "Felix Domke <tmbinc@elitedvb.net>"
RDEPENDS = ""
PACKAGES = "${PN}-meta ${PN}"
PACKAGES_DYNAMIC = "enigma2-plugin-skins-*"

inherit gitpkgv

PV = "experimental-git${SRCPV}"
PKGV = "experimental-git${GITPKGV}"
PR = "r2"
BRANCH = "3.2"

SRC_URI = "git://schwerkraft.elitedvb.net/enigma2-skins/enigma2-skins.git;protocol=git;branch=${BRANCH}"

#include examples of openpli widgets
SRC_URI_append = " \
	file://dtvhd.diff \
	file://brushedaluhd.diff \
	file://blackbox.diff \
	"

# note that enigma2-skins is just an empty package to satisfy silly dependencies.
ALLOW_EMPTY = "1"
FILES_${PN} = "/usr/share/enigma2 /usr/share/fonts"
FILES_${PN}-meta = "${datadir}/meta"
RDEPENDS_${PN}-meta = ""

inherit autotools

S = "${WORKDIR}/git"

python populate_packages_prepend () {
	if bb.data.expand('${REL_MINOR}', d) != "4":
		enigma2_skindir = bb.data.expand('${datadir}/enigma2', d)
		do_split_packages(d, enigma2_skindir, '(.*?)/.*', 'enigma2-plugin-skins-%s', 'Enigma2 Skin: %s', recursive=True, match_path=True, prepend=True)
}

gha_language: C