An effective approach for topic-specific opinion summarization

Binyang Li, Lanjun Zhou, Wei Gao, Kam Fai Wong, Zhongyu Wei

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

1 Citation (Scopus)

Abstract

Topic-specific opinion summarization (TOS) plays an important role in helping users digest online opinions, which targets to extract a summary of opinion expressions specified by a query, i.e. topic-specific opinionated information (TOI). A fundamental problem in TOS is how to effectively represent the TOI of an opinion so that salient opinions can be summarized to meet user's preference. Existing approaches for TOS are either limited by the mismatch between topic-specific information and its corresponding opinionated information or lack of ability to measure opinionated information associated with different topics, which in turn affect the performance seriously. In this paper, we represent TOI by word pair and propose a weighting scheme to measure word pair. Then, we integrate word pair into a random walk model for opinionated sentence ranking and adopt MMR method for summarization. Experimental results showed that salient opinion expressions were effectively weighted and significant improvement achieved for TOS.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages398-409
Number of pages12
Volume7097 LNCS
DOIs
Publication statusPublished - 28 Dec 2011
Externally publishedYes
Event7th Asia Information Retrieval Societies Conference, AIRS 2011 - Dubai, United Arab Emirates
Duration: 18 Dec 201120 Dec 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7097 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other7th Asia Information Retrieval Societies Conference, AIRS 2011
CountryUnited Arab Emirates
CityDubai
Period18/12/1120/12/11

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Keywords

  • MMR
  • Topic-specific opinion summarization
  • topic-specific opinionated information
  • word pair

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Li, B., Zhou, L., Gao, W., Wong, K. F., & Wei, Z. (2011). An effective approach for topic-specific opinion summarization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7097 LNCS, pp. 398-409). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7097 LNCS). https://doi.org/10.1007/978-3-642-25631-8_36