Inspecting and Visualizing Distributed Bayesian Student Models
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
RECON: a reciprocal recommender for online dating
Proceedings of the fourth ACM conference on Recommender systems
User-centric information management for decision support in disaster relief & evacuation
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Improving Group Selection and Assessment in an Asynchronous Collaborative Writing Application
International Journal of Artificial Intelligence in Education
A framework for user controlled remembering and forgetting in long term user models
Proceedings of the 13th international conference on Ubiquitous computing
Theoretical foundations for user-controlled forgetting in scrutable long term user models
Proceedings of the 23rd Australian Computer-Human Interaction Conference
ExpertiseNet: relational and evolutionary expert modeling
UM'05 Proceedings of the 10th international conference on User Modeling
"Afinando" a comunicação entre pares para melhorar a compreensão da mensagem do designer
Proceedings of the 10th Brazilian Symposium on on Human Factors in Computing Systems and the 5th Latin American Conference on Human-Computer Interaction
Online dating recommender systems: the split-complex number approach
Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web
Building Multi-Modal Relational Graphs for Multimedia Retrieval
International Journal of Multimedia Data Engineering & Management
Relational term-suggestion graphs incorporating multipartite concept and expertise networks
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
User Modeling and User-Adapted Interaction
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This paper describes user modelling in I-Help, a system to facilitate communication amongst learners. There are two I-Help components: Private and Public Discussions. In the Private Discussions learners take part in a one-on-one interaction with a partner (possibly a peer). The Public Discussions are open - everyone in the group has access to all discussion forums relevant to that group. The Public Discussions are most suited to discussion of issues where there might be a variety of valid viewpoints, or different solutions to a problem. It is also useful for straightforward questions and answers that have wide-spread applicability. The Private Discussions are better suited for more intensive interactions involving peer tutoring or in-depth discussions. Because there is only one helper in such situations, I-Help requires a method of selecting an appropriate helper for an individual. We describe the user modelling that takes place in each part of I-Help, in particular to effect this matchmaking for Private Discussions. This modelling takes advantage of a distributed multi-agent architecture, allowing currently relevant user model fragments in various locations to be integrated and computed at the time they are required.