A Method for Evaluating Full-text Search Queries in Native XML Databases.
Recommender systems apply statistical and knowledge discovery techniques to the problem of making recommendations during live user interaction. This paper describes a novel approach of building recommender systems for the Web with the aid of user-generated content. Recently certain communities of Internet users have engaged in creating high quality peer reviewed content for the Web. In our approach we are planning to extract the semantics of such user-generated content and to use these semantics to make more useful recommendations.Full text of the paper in pdf