E-Learning Resource Recommendation Based on Fuzzy Sets

Lian Hong Ding

doi:10.4028/www.scientific.net/AMM.513-517.2186

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517E-Learning Resource Recommendation Based on Fuzzy...

E-Learning Resource Recommendation Based on Fuzzy Sets

Abstract:

A challenging topic for e-learning system is to find appropriate learning assets for users when e-learning takes place in an open and dynamic environment. A good personalized e-learning environment should recommend right learning content for learners. In order to find appropriate learning materials for learners with different preferences, this paper presents a fuzzy set theoretic method for e-learning system. Firstly, e-learning resource and user interest are represented with fuzzy value. Secondly, an algorithm based on various fuzzy set theoretic similarity measures is introduced to find the e-learning contents matching learners request. Lastly, the approach to introduce learning materials for learners, based on the similarity computing, is given. Compared to the baseline crisp set based method presented, our method shows an improvement in precision without loss of recall.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

2186-2189

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.2186

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Online since:

February 2014

Authors:

Lian Hong Ding*

Keywords:

E-Learning, Fuzzy Set, Learning Contents, Recommendation

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* - Corresponding Author

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