Rated aspect summarization of short comments

Yue Lu, Chengxiang Zhai, Neel Sundaresan

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

Abstract

Web 2.0 technologies have enabled more and more people to freely comment on different kinds of entities (e.g. sellers, products, services). The large scale of information poses the need and challenge of automatic summarization. In many cases, each of the user-generated short comments comes with an overall rating. In this paper, we study the problem of generating a "rated aspect summary" of short comments, which is a decomposed view of the overall ratings for the major aspects so that a user could gain different perspectives towards the target entity. We formally define the problem and decompose the solution into three steps. We demonstrate the effectiveness of our methods by using eBay sellers' feedback comments. We also quantitatively evaluate each step of our methods and study how well human agree on such a summarization task. The proposed methods are quite general and can be used to generate rated aspect summary automatically given any collection of short comments each associated with an overall rating. Copyright is held by the International World Wide Web Conference Committee (IW3C2).

Original languageEnglish (US)
Title of host publicationWWW'09 - Proceedings of the 18th International World Wide Web Conference
Pages131-140
Number of pages10
DOIs
StatePublished - Dec 1 2009
Event18th International World Wide Web Conference, WWW 2009 - Madrid, Spain
Duration: Apr 20 2009Apr 24 2009

Publication series

NameWWW'09 - Proceedings of the 18th International World Wide Web Conference

Other

Other18th International World Wide Web Conference, WWW 2009
Country/TerritorySpain
CityMadrid
Period4/20/094/24/09

Keywords

  • Rated aspect summarization
  • Rating prediction
  • Short comments

ASJC Scopus subject areas

  • Computer Networks and Communications

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