Opinion Retrieval

Shima Gerani, Mark J. Carman, Fabio Crestani

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

3 Citations (Scopus)

Abstract

Blog post opinion retrieval is the problem of identifying posts which express an opinion about a particular topic. Usually the problem is solved using a 3 step process in which relevant posts are first retrieved, then opinion scores are generated for each document, and finally the opinion and relevance scores are combined to produce a single ranking. In this paper, we study the effectiveness of classification and rank learning techniques for solving the blog post opinion retrieval problem. We have chosen not to rely on external lexicons of opinionated terms, but investigateto what extent the list of opinionated terms can be mined from the same corpus of relevance/opionion assessments that are used to train. the retrieval system. We compare popular feature selection methods such as the weighted log likelihood ratio and mutual information for use both in selecting terms for training an opinionated document classifier and also as term weights for generating simpler (not learning based) aggregate opinion scores for documents.We thereby analyze what performance gains result from learning in the opinion detection phase. Furthermore we compare different learning and not learning based methods for combining relevance and opinion information in order to generate a rankedlist of opinionated posts, thereby investigating the effect of learning onthe ranking phase.

Original languageEnglish
Title of host publicationAdvances in Information Retrieval - 31th European Conference on IR Research, ECIR 2009, Proceedings
Pages337-349
Number of pages13
Volume5478 LNCS
DOIs
Publication statusPublished - 2009
Externally publishedYes
EventEuropean Conference on Information Retrieval 2009 - Toulouse France, Toulouse, France
Duration: 6 Apr 20099 Apr 2009
Conference number: 31st

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5478 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

ConferenceEuropean Conference on Information Retrieval 2009
Abbreviated titleECIR 2009
CountryFrance
CityToulouse
Period6/04/099/04/09

Keywords

  • Blog Post
  • Learning Methods
  • Opinion Retrieval

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