Relational Distance-Based Collaborative Filtering for E-Learning

Recommender systems for e-learning need to consider the specific demands and requirements and to improve the 'educational aspects' for the learners. In this paper, we present a novel hybrid recommender system called RelationalCF, which integrates learners and learning items information int...

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Bibliographic Details
Published in:2008 International Symposium on Computational Intelligence and Design Vol. 2; pp. 354 - 357
Main Author: Wei Zhang
Format: Conference Proceeding
Language:English
Published: IEEE 01-10-2008
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Summary:Recommender systems for e-learning need to consider the specific demands and requirements and to improve the 'educational aspects' for the learners. In this paper, we present a novel hybrid recommender system called RelationalCF, which integrates learners and learning items information into a collaborative filtering framework by using relational distance computation approaches. Our experiments suggest that the effective combination of various kinds of learning information based on relational distance approaches provides improved accurate recommendations than other approaches.
ISBN:0769533116
9780769533117
DOI:10.1109/ISCID.2008.54