Selecting a diversified set of reviews

Wenzhe Yu*, Rong Zhang, Xiaofeng He, Chaofeng Sha

*Corresponding author for this work

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

9 Scopus citations

Abstract

Online product reviews provide helpful information for user decision-making. However, since user-generated reviews proliferate in recent years, it is critical to deal with the information overload in e-commerce sites. In this paper, we propose an approach to select a small set of representative reviews for each product, which shall consider both the attribute coverage and opinion diversity under the requirement of providing high quality reviews. First, we assign weights to each attribute, which measure the attribute importance and help realize useful review selection; second, we cluster reviews into different groups representing different concerns which lead to better diversification results especially for selecting smaller sets of reviews; finally, we perform a set of experiments on real datasets to verify our ideas.

Original languageEnglish
Title of host publicationWeb Technologies and Applications - 15th Asia-Pacific Web Conference, APWeb 2013, Proceedings
Pages721-733
Number of pages13
DOIs
StatePublished - 2013
Event15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013 - Sydney, NSW, Australia
Duration: 4 Apr 20136 Apr 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7808 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013
Country/TerritoryAustralia
CitySydney, NSW
Period4/04/136/04/13

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