Exploiting Web Browsing Activities for User Needs Identification

Browsing sessions are rich in elements useful to build profiles of user interests, but at the same time HTML pages include noise data, such as ads and navigation menus. Moreover, pages might cover several different topics. For these reasons they are often ignored in personalized approaches. We propose a novel approach for implicitly recognizing valuable text descriptions of current user needs based on the implicit feedback revealed through web browsing interactions.