Measuring term informativeness in context

Zhaohui Wu, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations

Abstract

Measuring term informativeness is a fundamental NLP task. Existing methods, mostly based on statistical information in corpora, do not actually measure informativeness of a term with regard to its semantic context. This paper proposes a new lightweight feature-free approach to encode term informativeness in context by leveraging web knowledge. Given a term and its context, we model contextaware term informativeness based on semantic similarity between the context and the term's most featured context in a knowledge base, Wikipedia. We apply our method to three applications: core term extraction from snippets (text segment), scientific keywords extraction (paper), and back-of-The-book index generation (book). The performance is state-of-Theart or close to it for each application, demonstrating its effectiveness and generality.

Original languageEnglish (US)
Title of host publicationNAACL HLT 2013 - 2013 Conference of the North American Chapter of the Association for Computational Linguistics
Subtitle of host publicationHuman Language Technologies, Proceedings of the Main Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages259-269
Number of pages11
ISBN (Electronic)9781937284473
StatePublished - Jan 1 2013
Event2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2013 - Atlanta, United States
Duration: Jun 9 2013Jun 14 2013

Publication series

NameNAACL HLT 2013 - 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Main Conference

Other

Other2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2013
CountryUnited States
CityAtlanta
Period6/9/136/14/13

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Computer Science Applications
  • Linguistics and Language

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    Wu, Z., & Giles, C. L. (2013). Measuring term informativeness in context. In NAACL HLT 2013 - 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Main Conference (pp. 259-269). (NAACL HLT 2013 - 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Main Conference). Association for Computational Linguistics (ACL).