A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
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Preface: Special Issue on User Modeling and Personalization for Television
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MIWAI'11 Proceedings of the 5th international conference on Multi-Disciplinary Trends in Artificial Intelligence
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This paper is concerned with personalisation of user agents by symbolic, on-line machine learning techniques. The application of these ideas to an infotainment agent is discussed in detail. Also experimental results, which indicate that a high level of personalisation can be achieved by this approach, are presented.