| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 384191 | Expert Systems with Applications | 2013 | 7 Pages |
In this paper, we develop SumView, a Web-based review summarization system, to automatically extract the most representative expressions and customer opinions in the reviews on various product features. Different from existing review analysis which makes more efforts on sentiment classification and opinion mining, our system mainly focuses on summarization, i.e., delivering the majority of information contained in the review documents by selecting the most representative review sentences for each extracted product feature. Comprehensive case studies and experiments demonstrate the effectiveness of our system, and the user study shows users’ satisfaction.
► We develop SumView, a Web-based system, to summarize product reviews and customer opinions. ► A prototype of the system can be found at http://rev-sum.appspot.com/. ► SumView integrates review crawling, product feature extraction, and sentence selection. ► Sentence selection is done using feature-based weighted non-negative matrix factorization.
