Acquiring User Preferences for Personal Agents

Paolo Viappiani, Pearl Pu, and Boi Faltings

Personal agents represent a novel paradigm that merges ideas from the agent based computing and the intelligent information system areas. A personal agent gathers and filters information on user’s behalf, models user’s needs and preferences in order to generate recommendations. To build an efficient user model, both explicitly stated and hidden (inferred from context or other users) preferences have to be considered because people are not good at describing their own decision criteria; moreover preferences can change over time. In this paper different techniques for modeling and obtaining preferences are presented, with special emphasis on systems that interact with the user in form of dialogue, in a way that makes it possible to elicit preferences just in time. Several questions that require further investigations are raised.


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