Personalized Information Gathering in a Multiple Personal Device Environment

Abstract

We propose a personalized information gathering system PerIGS that exploits implicit user feedback in a multiple personal device environment. PerIGS extracts imposing words that induce user's choice from recommended news articles, and constructs user preference profile based on observed user behaviors. A user profile is shared by multiple personal devices, and PerIGS gathers, filters, and recommends news articles according to this shared profile. We organize the user profile in a hierarchical category structure to deal with the uncertainty of user interests. This structure also enables the system to track and recognize the changes of user interests for each domain more effectively. The results of a series of experiments measuring user satisfaction for recommended news articles indicated that PerIGS can effectively utilize user profiles for news filtering and recommendation.