Personalized categorization of XML query results

To deal with the problem of too many answer elements returned from a XML repository in response to a user query, this paper proposes a personalized categorization approach which takes advantages of the user preferences to construct a categorization tree in order to reduce the information overload. The approach consists of two steps. The first step analyzes query history of all users in the system offline and generates a set of clusters over the XML elements, where each elements cluster represents one kind of user preference. When a user query coming, based on the element clusters, a categorization tree is generated automatically by using the C4.5 algorithm and presented to the user, such that the user can easily select the relevant elements matching his needs. Results of a preliminary user study demonstrate that the categorization method proposed has good categorization effectiveness and low searching cost.