Minimal knowledge anonymous user profiling for personalized services

Abstract

Abstract:- The paper presents a solution to the problem of application of user profiles for anonymous internet users. The basic assumption is that only minimal knowledge about the user is given, i.e. information such as user session, user tracing and clickstream analysis is not available. This situation is of great interest because it characterizes most internet users, such as user of search engine. In the typical case the user is described only by IP address, date/time of connection and keywords. The proposed architecture is based on the use of predefined profiles and the computation of fuzzy similarities in order to match the user observed with appropriate target profiles. The proposed model for user profiling in presence of minimal knowledge has many applications like generation of banners for online advertising, dynamical web pages for public services etc. The notion of fuzzy similarity presented here is based on the theoretical framework of the Lukasiewicz structure; it guaranties the correctness of the approach. A prototype implementation of a banner engine is finally presented and discussed