The availability of large-scale data on the Web motivates the development of automatic algorithms to analyze topics and to identify relationships between topics.Various approaches have been proposed in the literature. Most focus on specific topics, mainly those representing people, with little attention to topics of other kinds. They given topics of interest, as part of the 2007 TREC Expert Search task.Overall, our results show that topic profiles provide a strong foundation for exploring different topics and for mining relationships between topics using web data.Our approach can be applied to a wide range of web knowledge discovery problems, in contrast to existing approaches that are mostly designed for specific problems.
Abstract Approved:Thesis Supervisor