Opinion Summarization of Customer Comments
Web 2.0 technologies have enabled more and more customers to freely comment on different kinds of entities, such as sellers, products and services. The large scale of information poses the need and challenge of automatic summarization. In many cases, each of the user-generated short comments implies the opinions which rate the target entity. In this paper, we aim to mine and to summarize all the customer comments of a product. The algorithm proposed in this research is more reliable on opinion identification because it is unsupervised and the accuracy of the result improves as the number of comments increases. Our research is performed in four steps: (1) mining the frequent aspects of a product that have been commented on by customers; (2) mining the infrequent aspects of a product which have been commented by customers (3) identifying opinion words in each comment and deciding whether each opinion word is positive, negative or neutral; (4) summarizing the comments. This paper proposes several novel techniques to perform these tasks. Our experimental results using comments of a number of products sold online demonstrate the effectiveness of the techniques.
Data mining product aspect opinion identification comment
Miao Fan Guoshi Wu
School of Software Engineering Beijing University of Posts and Telecommunications Beijing, China, 100876
国际会议
2010 International Conference on Circuit and Signal Processing(2010年电路与信号处理国际会议 ICCSP 2010)
上海
英文
5-9
2010-12-25（万方平台首次上网日期，不代表论文的发表时间）