Querying and personalizing the Web: a multimedia personal assistant

We suggest that four points should be considered when developing new information retrieval systems: a) taking information in its entirety (interpretation), b) managing multimedia information in an integrated way, c) reusing already available tools and d) tailoring information to single users. We propose a framework for endowing a software agent with the capacity to personalize itself to its users through interaction, and to perform tasks that involve subjective factors. We describe K-DIME, a software prototype that can retrieve material from the Web based on both objective and subjective features of content. Being capable of bootstrapping a new user model from a model of a user with similar profile, K-DIME significantly reduces the workload generally associated with the online learning phase. Through continuous adaptation driven by specific patterns of interaction with the user, K-DIME can cope with the intrinsic variability of subjective impressions. We discuss K-DIME's performance in a scenario in which users retrieve pictures for greeting cards according to a given subjective impression that they wish to convey.