Improving Opinion-based Entity Ranking

We examine the problem of entity ranking using opinions expressed in users' reviews. There is a massive development of opinions and reviews on the web, which includes reviews of products and services, and opinions about events and persons. For products especially, there are thousands of users' reviews, that consumers usually consult before proceeding in a purchase. In this study we are following the idea of turning the entity ranking problem into a matching preferences problem. This allows us to approach its solution using any standard information retrieval model. Building on this framework, we examine techniques which use sentiment and clustering information, and we suggest the naive consumer model. We describe the results of two sets of experiments and we show that the proposed techniques deliver interesting