Using subjectivity analysis to improve thread retrieval in online forums

Prakhar Biyani, Sumit Bhatia, Cornelia Caragea, Prasenjit Mitra

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

4 Citations (Scopus)

Abstract

Finding relevant threads in online forums is challenging for internet users due to a large number of threads discussing lexically similar topics but differing in the type of information they contain (e.g., opinions, facts, emotions). Search facilities need to take into account the match between users’ intent and the type of information contained in threads in addition to the lexical match between user queries and threads. We use intent match by incorporating subjectivity match between user queries and threads into a state-of-the-art forum thread retrieval model. Experimental results show that subjectivity match improves retrieval performance by over 10% as measured by different metrics.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages495-500
Number of pages6
Volume9022
ISBN (Print)9783319163536
Publication statusPublished - 2015
Event37th European Conference on Information Retrieval Research, ECIR 2015 - Vienna, Austria
Duration: 29 Mar 20152 Apr 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9022
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other37th European Conference on Information Retrieval Research, ECIR 2015
CountryAustria
CityVienna,
Period29/3/152/4/15

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Biyani, P., Bhatia, S., Caragea, C., & Mitra, P. (2015). Using subjectivity analysis to improve thread retrieval in online forums. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9022, pp. 495-500). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9022). Springer Verlag.