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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Published in: | 2008 International Symposium on Computational Intelligence and Design Vol. 2; pp. 354 - 357 |
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Main Author: | |
Format: | Conference Proceeding |
Language: | English |
Published: |
IEEE
01-10-2008
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Subjects: | |
Online Access: | Get full text |
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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. |
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ISBN: | 0769533116 9780769533117 |
DOI: | 10.1109/ISCID.2008.54 |