Opinion Integration Through Semi-supervised Topic Modeling
(0) Web 2.0 technology has enabled more and more people to freely express their opinions on theWeb, making theWeb an extremely valuable source for mining user opinions about all kinds of topics. In this paper we study how to automatically integrate opinions expressed in a well-written expert review with lots of opinions scattering in various sources such as blogspaces and forums. We formally define this new integra-tion problem and propose to use semi-supervised topic mod-els to solve the problem in a principled way. Experiments on integrating opinions about two quite different topics (a prod-uct and a political figure) show that the proposed method is effctive for both topics and can generate useful aligned in-tegrated opinion summaries. The proposed method is quite general. It can be used to integrate a well written review with opinions in an arbitrary text collection about any topic to potentially support many interesting applications in mul-tiple domains.
opinion integration semi-supervised proba-bilistic topic modeling expert review
Yue Lu Chengxiang Zhai
Department of Computer Science University of Illinois at Urbana-Champaign Urbana, IL 61801
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）