Mining product reviews based on shallow dependency parsing

Qi Zhang, Yuanbin Wu, Tao Li, Mitsunori Ogihara, Joseph Johnson, Xuanjing Huang

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

18 Scopus citations

Abstract

This paper presents a novel method for mining product reviews, where it mines reviews by identifying product features, expressions of opinions and relations between them. By taking advantage of the fact that most of product features are phrases, a concept of shallow dependency parsing is introduced, which extends traditional dependency parsing to phrase level. This concept is then implemented for extracting relation between product features and expressions of opinions. Experimental evaluations show that the mining task can benefit from shallow dependency parsing.

Original languageEnglish (US)
Title of host publicationProceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009
Pages726-727
Number of pages2
DOIs
StatePublished - Dec 28 2009
Event32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009 - Boston, MA, United States
Duration: Jul 19 2009Jul 23 2009

Publication series

NameProceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009

Other

Other32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009
CountryUnited States
CityBoston, MA
Period7/19/097/23/09

Keywords

  • Dependency parsing
  • Product mining

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Information Systems and Management

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