Category ranking for personalized search

Despite the effectiveness of search engines, the persistently increasing amount of web data continuously obscures the search task. Efforts have thus concentrated on personalized search that takes account of user preferences. A new concept is introduced towards this direction; search based on ranking of local set of categories that comprise a user search profile. New algorithms are presented that utilize web page categories to personalize search results. Series of user-based experiments show that the proposed solutions are efficient. Finally, we extend the application of our techniques in the design of topic-focused crawlers, which can be considered an alternative personalized search.