Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Secure communications over insecure channels
Communications of the ACM
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Defining Knowledge Layers for Textual Case-Based Reasoning
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
The Intelligent Helpdesk: Supporting Peer-Help in a University Course
ITS '98 Proceedings of the 4th International Conference on Intelligent Tutoring Systems
Multi-Agent Multi-User Modeling in I-Help
User Modeling and User-Adapted Interaction
Supporting Collaborative Learning by Matching Human Actors
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track1 - Volume 1
How to think about security failures
Communications of the ACM - Personal information management
Who Helps the Helper? A Situated Scaffolding System for Supporting Less Experienced Feedback Givers
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Harnessing Learner's Collective Intelligence: A Web2.0 Approach to E-Learning
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Market-Based Adaptive Discussion Forums
Advanced Internet Based Systems and Applications
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During the training phase in an Intelligent Tutoring System, learners usually require help. However, it may happen that the tutor cannot provide such help, unless it has access to additional pedagogical resources. Moreover, in a collaborative but competitive learning environment in which each user could be both learner and expert, security problems may arise. For instance, the exchanges between users could require security services such as anonymity, confidentiality and integrity. In this paper, we introduce a system, called SPRITS, whose aim is to provide the tutor with mechanisms to capture, exploit, organize, deliver and evaluate learners knowledge, in a secure way, based on the learner-expert concept. Our main contribution is the introduction of security services in an ITS for the benefit of learners. This may be helpful to protect learners' privacy as well as communication contents and pedagogical resources in an artificial competitive peer environment, thus allowing the tutor to better evaluate learners.