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User Modeling 2007

11th International Conference, UM 2007, Corfu, Greece, July 25-29, 2007, Proceedings

  • Conference proceedings
  • © 2007

Overview

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4511)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: UM 2007.

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Table of contents (69 papers)

  1. Full Papers

    1. Evaluating User/Student Modeling Techniques

    2. Data Mining and Machine Learning for User Modeling

    3. Collaborative Filtering and Recommender Systems

    4. Cognitive Modeling

    5. User Adaptation and Usability

Keywords

About this book

As the variety and complexity of interactive systems increase, understanding how a system can dynamically capture relevant user needs and traits, and - tomatically adapting its interaction to this information, has become critical for devising e?ective advanced services and interfaces. The International User M- eling Conference represents the central forum for presenting the advances in the research and development of personalized, user-adaptive systems. Bi-annual scienti?c meetings of the user modeling community started in 1986 as a small invitational workshop held in Maria Laach, Germany, with 24 participants. The workshops continued with an open format, and grew into an international c- ference with 74 submissions in 1994. While maintaining its feel as a highly - gaged and intimate community, the conference has continued to grow, reaching the record number of 169 submissions (153 full papers and 16 posters) in this current edition, held in Corfu, Greece. With an acceptance rate of 19. 6% for long papers and 38% for posters, - lected by a team of reviewers who proved to be exceptionally thorough and thoughtful in their reviewers, this year’s program followed the high standards set by the previous editions, and presented an exciting range of interdisciplinary work covering topics such as cognitive modeling, modeling of user a?ect and meta-cognition,empirical evaluations of noveltechniques, user modeling for - bilecomputingandrecommendersystems,useradaptivityandusability.

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