Mining context specific similarity relationships using the world wide web

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationHLT/EMNLP 2005 - Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference
Pages499-506
StatePublished - 2005
Externally publishedYes

Conference

TitleHuman Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, HLT/EMNLP 2005, Co-located with the 2005 Document Understanding Conference, DUC and the 9th International Workshop on Parsing Technologies, IWPT
PlaceCanada
CityVancouver, BC
Period6 - 8 October 2005

Abstract

We have studied how context specific web corpus can be automatically created and mined for discovering semantic similarity relationships between terms (words or phrases) from a given collection of documents (target collection). These relationships between terms can be used to adjust the standard vectors space representation so as to improve the accuracy of similarity computation between text documents in the target collection. Our experiments with a standard test collection (Reuters) have revealed the reduction of similarity errors by up to 50%, twice as much as the improvement by using other known techniques. © 2005 Association for Computational Linguistics.

Citation Format(s)

Mining context specific similarity relationships using the world wide web. / Roussinov, Dmitri; Zhao, Leon J.; Fan, Weiguo.

HLT/EMNLP 2005 - Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. 2005. p. 499-506.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)