Topic relatedness in evaluative information extraction

Takuya Kawada, Tetsuji Nakagawa, Kentaro Inui, Sadao Kurohashi

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

1 Citation (Scopus)

Abstract

The task of extracting opinions/evaluations related to a given topic from a large number of documents such as Web documents is crucial for developing an automatic evaluation finding system, which can handle a wide variety of topics as input. In this paper, we discuss the topic relatedness of extracted evaluation through analysis of a corpus we developed. We suggest here that the semantic relationship between the target of each extracted evaluation and a given topic helps in judging topic relatedness. In addition, we point out other factors that are beyond the analysis of topic-target relations for judging the topic relatedness of evaluation.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Universal Communication Symposium, IUCS 2009
Pages120-125
Number of pages6
DOIs
Publication statusPublished - 2009 Dec 1
Externally publishedYes
Event3rd International Universal Communication Symposium, IUCS 2009 - Tokyo, Japan
Duration: 2009 Dec 32009 Dec 4

Publication series

NameACM International Conference Proceeding Series

Other

Other3rd International Universal Communication Symposium, IUCS 2009
CountryJapan
CityTokyo
Period09/12/309/12/4

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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