Opinion summarization of customer reviews

This paper focuses on the problem of opinion summarization of customer reviews, which has not been solved completely in how to get a summary that overlaps the most important topics of review text and to extract the opinion on these topics. With the intuition that both factual text and evaluative text should be considered in opinion summarization, this paper deals with sentiment and topics of review text simultaneously and proposes a multi-document opinion summarization approach based on Latent Dirichlet Allocation model. Experiments on product reviews show that the approach is effective.