Ontology mining for personalized search

Abstract

Knowledge discovery for user information needs in user local information repositories is a challenging task. Traditional data mining techniques cannot provide a satisfactory solution for this challenge, because there exists a lot of uncertainties in the local information repositories. In this chapter, we introduce ontology mining, a new methodology, for solving this challenging issue, which aims to discover interesting and useful knowledge in databases in order to meet the specified constraints on an ontology. In this way, users can efficiently specify their information needs on the ontology rather than dig useful knowledge from the huge amount of discorded patterns or rules. The proposed ontology mining model is evaluated by applying to an information gathering system, and the results are promising. © 2009 Springer US.