Modeling User Preferences through Adaptive Fuzzy Profiles

Adaptive software systems are systems that tailor their behavior to each user on the basis of a personalization process. The efficacy of this process is strictly connected with the possibility of an automatic detection of preference profiles, through the analysis of the users' behavior during their interactions with the system. The definition of such profiles should take into account imprecision and gradedness, two features that justify the use of fuzzy sets for their representation. This paper proposes a model for representing preference profiles through fuzzy sets. The model's strategy for adapting profiles to user preferences is to record the sequence of accessed resources by each user, and to update preference profiles accordingly so as to suggest similar resources at next user accesses. Profile adaption is performed continuously, but in earlier stages it is more sensitive to updates (plastic phase) while in later stages it is less sensitive (stable phase) to allow resource suggestion. Simulation results are reported to show the effectiveness of the proposed approach.