Modularized User Modeling in Conversational Recommender Systems 529 4 Contributions Concrete contributions of this work will include a theory for explaining and designing DP recommender systems with modu larized and transparent adaptivity according to the problem space described in section 2 a tool that implements the theory, and that provides developers with con- figurable and transparent user modeling components that generate desired adaptive functionality for their end-users, an an application built with the tool for end-user evaluation of the approach. Acknowledgments. This work is supervised by arne Jonsson and Lars Degerst edt, and supported by GSLT(Sweden)and Santa Anna IT Research References 1. Robin D. Burke, Kristian J. Hammond, and Benjamin C. Young. The FindMe Approach to Assisted Browsing. IEEE Expert, 12(4): 32-40, 1997 2. Giuseppe Carenini, Jocelyin Smith, and David Poole. Towards more conversa- tional and collaborative recommender systems. In Proceedings of the international Conference of Intelligent User Interfaces, pages 12-18, Miami, Florida, USA, 2003 3. Lars Degerstedt and Pontus Johansson. Evolutionary Development of Phase-Based Dialogue Systems. In Proceedings of the 8th Scandinavian Conference on Artificial Intelligence, pages 59-67, Bergen, Norway, 2003 4. Gerhard Fischer. User modeling in human-computer interaction. User Modeling nd User-Adapted Interaction, 11: 65-86, 2001 5. Pontus Johansson. Design and development of recommender dialogue systems. Licentiate Thesis 1079, Linkoping Studies in Science and Technology, Linkoping University, April 2004 6. Lorraine McGinty and Barry Smyth. Deep dialogue vs casual conversation in rec- mender systems. In F. Ricci and B Smyth, editors, Personalization in e corm- merce at the Second International Conference on Adaptive Hypermedia and Wet Based Systems(AH-02), pages 80-89, Malaga, Spain, 2002. 7. Katarina Morik. Discourse models, dialog memories, and user models. Computa- tional Linguistics, 14: 95-97, 1988 8. Cynthia Thompson, Mehmet Goker, and Pat Langley. A personalized system for conversational recommendations. Journal of Artificial Intelligence Research 21:393-428,2004. 9. Pontus Warnestal. Modeling a dialogue strategy for personalized movie recom- mendations. In Beyond Personalization 05 Workshop, pages 77-82, San Diego, CA, USA, January 2005 10. Ingrid Zukerman and Diane Litman. Natural language processing and user mod eling: Synergies and limitations. User Modeling and User-Adapted Interaction 11:129-158,2001.Modularized User Modeling in Conversational Recommender Systems 529 4 Contributions Concrete contributions of this work will include: – a theory for explaining and designing dp recommender systems with modu￾larized and transparent adaptivity according to the problem space described in section 2, – a tool that implements the theory, and that provides developers with con- figurable and transparent user modeling components that generate desired adaptive functionality for their end-users, and – an application built with the tool for end-user evaluation of the approach. Acknowledgments. This work is supervised by Arne J¨onsson and Lars Degerst￾edt, and supported by GSLT (Sweden) and Santa Anna IT Research. References 1. Robin D. Burke, Kristian J. Hammond, and Benjamin C. Young. The FindMe Approach to Assisted Browsing. IEEE Expert, 12(4):32–40, 1997. 2. Giuseppe Carenini, Jocelyin Smith, and David Poole. Towards more conversa￾tional and collaborative recommender systems. In Proceedings of the International Conference of Intelligent User Interfaces, pages 12–18, Miami, Florida, USA, 2003. 3. Lars Degerstedt and Pontus Johansson. Evolutionary Development of Phase-Based Dialogue Systems. In Proceedings of the 8th Scandinavian Conference on Artificial Intelligence, pages 59–67, Bergen, Norway, 2003. 4. Gerhard Fischer. User modeling in human-computer interaction. User Modeling and User-Adapted Interaction, 11:65–86, 2001. 5. Pontus Johansson. Design and development of recommender dialogue systems. Licentiate Thesis 1079, Link¨oping Studies in Science and Technology, Link¨oping University, April 2004. 6. Lorraine McGinty and Barry Smyth. Deep dialogue vs casual conversation in rec￾ommender systems. In F. Ricci and B Smyth, editors, Personalization in eCom￾merce at the Second International Conference on Adaptive Hypermedia and Web￾Based Systems (AH-02), pages 80–89, Malaga, Spain, 2002. 7. Katarina Morik. Discourse models, dialog memories, and user models. Computa￾tional Linguistics, 14:95–97, 1988. 8. Cynthia Thompson, Mehmet G¨oker, and Pat Langley. A personalized system for conversational recommendations. Journal of Artificial Intelligence Research, 21:393–428, 2004. 9. Pontus W¨arnest˚al. Modeling a dialogue strategy for personalized movie recom￾mendations. In Beyond Personalization’05 Workshop, pages 77–82, San Diego, CA, USA, January 2005. 10. Ingrid Zukerman and Diane Litman. Natural language processing and user mod￾eling: Synergies and limitations. User Modeling and User-Adapted Interaction, 11:129–158, 2001