research-article

Wiki3C: exploiting wikipedia for context-aware concept categorization

Authors:

Min WangAuthors Info & Claims

WSDM '13: Proceedings of the sixth ACM international conference on Web search and data mining

Pages 345 - 354

https://doi.org/10.1145/2433396.2433441

Published: 04 February 2013 Publication History

Abstract

Wikipedia is an important human generated knowledge base containing over 21 million articles organized by millions of categories. In this paper, we exploit Wikipedia for a new task of text mining: Context-aware Concept Categorization. In the task, we focus on categorizing concepts according to their context. We exploit article link feature and category structure in Wikipedia, followed by introducing Wiki3C, an unsupervised and domain independent concept categorization approach based on context. In the approach, we investigate two strategies to select and filter Wikipedia articles for the category representation. Besides, a probabilistic model is employed to compute the semantic relatedness between two concepts in Wikipedia. Experimental evaluation using manually labeled ground truth shows that our proposed Wiki3C can achieve a noticeable improvement over the baselines without considering contextual information.

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Cited By

Fuentes-Lorenzo DMorato JSanchez-Cuadrado SSanchez L(2019)Building concept maps by adapting semantic distance metrics to WikipediaEducation for Information10.3233/EFI-19027935:3(209-240)Online publication date: 2-Aug-2019
https://doi.org/10.3233/EFI-190279
Chang WKoh J(2015)Dynamic Facet Hierarchy Constructing for Browsing Web Search Results EfficientlyProceedings of the 28th International Conference on Current Approaches in Applied Artificial Intelligence - Volume 910110.1007/978-3-319-19066-2_29(293-304)Online publication date: 10-Jun-2015
https://dl.acm.org/doi/10.1007/978-3-319-19066-2_29
Kumar RLamba DGarera NTiwari MChai XDas SSubramaniam SRajaraman AHarinarayan VDoan A(2013)Entity extraction, linking, classification, and tagging for social mediaProceedings of the VLDB Endowment10.14778/2536222.25362376:11(1126-1137)Online publication date: 1-Aug-2013
https://dl.acm.org/doi/10.14778/2536222.2536237
Show More Cited By

Index Terms

Wiki3C: exploiting wikipedia for context-aware concept categorization
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources

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cover image ACM Conferences

WSDM '13: Proceedings of the sixth ACM international conference on Web search and data mining

February 2013

816 pages

ISBN:9781450318693

DOI:10.1145/2433396

General Chairs:
Stefano Leonardi
Sapienza University of Rome, Italy
,
Alessandro Panconesi
Sapienza University of Rome, Italy
,
Program Chairs:
Paolo Ferragina
University of Pisa, Italy
,
Aristides Gionis
Yahoo! Research, Barcelona, Spain

Copyright © 2013 ACM.

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Published: 04 February 2013

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WSDM 2013: Sixth ACM International Conference on Web Search and Data Mining

February 4 - 8, 2013

Rome, Italy

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Cited By

Fuentes-Lorenzo DMorato JSanchez-Cuadrado SSanchez L(2019)Building concept maps by adapting semantic distance metrics to WikipediaEducation for Information10.3233/EFI-19027935:3(209-240)Online publication date: 2-Aug-2019
https://doi.org/10.3233/EFI-190279
Chang WKoh J(2015)Dynamic Facet Hierarchy Constructing for Browsing Web Search Results EfficientlyProceedings of the 28th International Conference on Current Approaches in Applied Artificial Intelligence - Volume 910110.1007/978-3-319-19066-2_29(293-304)Online publication date: 10-Jun-2015
https://dl.acm.org/doi/10.1007/978-3-319-19066-2_29
Kumar RLamba DGarera NTiwari MChai XDas SSubramaniam SRajaraman AHarinarayan VDoan A(2013)Entity extraction, linking, classification, and tagging for social mediaProceedings of the VLDB Endowment10.14778/2536222.25362376:11(1126-1137)Online publication date: 1-Aug-2013
https://dl.acm.org/doi/10.14778/2536222.2536237
Cornolti MFerragina PCiaramita MSchwabe DAlmeida VGlaser HBaeza-Yates RMoon S(2013)A framework for benchmarking entity-annotation systemsProceedings of the 22nd international conference on World Wide Web10.1145/2488388.2488411(249-260)Online publication date: 13-May-2013
https://dl.acm.org/doi/10.1145/2488388.2488411
Yang QJiang PZhang CNiu Z(2013)Extracting Fine-Grained Entities Based on Coordinate GraphNatural Language Processing and Information Systems10.1007/978-3-642-38824-8_40(367-371)Online publication date: 2013
https://doi.org/10.1007/978-3-642-38824-8_40

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