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Discovering Social Network to Improve Recommender System for Group Learning Support

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3 Author(s)
Xin Wan ; Grad. Sch. of Inf. Syst., Univ. of Electro-Commun., Chofu, Japan ; Jamaliding, Q. ; Okamoto, T.

We refer to a new generation of Web technologies such as social networking to address a recommender system that emphasize online collaborative learning. We propose an approach for improving recommender system through exploiting the learners note taking activity. We maintain that notes' features can be exploited by collaborative learning systems in order to enrich and extend the user profile and improve personalized learning. Thus our approach stresses collaborative note as a new and powerful kind of feedback and as a way to infer learner profiles. The experiment results show that our approach is effective.

Published in:

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Date of Conference:

11-13 Dec. 2009