ATTRIBUTE-BASED RECOMMENDER SYSTEM FOR LEARNING RESOURCE BY LEARNER PREFERENCE TREE

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SALEHI MOJTABA; NAKHAI KAMALABADI ISA

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE)
Year:2014 | Issue:4

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Information Seminar Paper

Title

ATTRIBUTE-BASED RECOMMENDER SYSTEM FOR LEARNING RESOURCE BY LEARNER PREFERENCE TREE

Author(s)

SALEHI MOJTABA | NAKHAI KAMALABADI ISA

Keywords

COLLABORATIVE FILTERING

E-LEARNING

SPARSITY

PERSONALIZED RECOMMENDER

Abstract

IN RECENT YEARS, WITH GROWTH OF ONLINE LEARNING TECHNOLOGY, A HUGE AMOUNT OF E-LEARNING RESOURCES HAVE BEEN GENERATED IN VARIOUS MEDIA FORMATS. THIS GROWTH HAS CAUSED DIFFICULTY OF LOCATING APPROPRIATE LEARNING RESOURCES TO LEARNERS. A PERSONALIZED RECOMMENDATION IS AN ENABLING MECHANISM TO OVERCOME INFORMATION OVERLOAD OCCURRED IN THE NEW LEARNING ENVIRONMENTS AND DELIVER SUITABLE LEARNER RESOURCES TO LEARNERS. SINCE USERS EXPRESS THEIR OPINIONS BASED ON SOME SPECIFIC ATTRIBUTES OF ITEMS, THIS PAPER CONSIDERS CONTEXTUAL INFORMATION INCLUDING ATTRIBUTES OF LEARNING RESOURCES AND RATING OF LEARNER SIMULTANEOUSLY TO ADDRESS SOME PROBLEM SUCH AS SPARSITY AND COLD START PROBLEM AND ALSO IMPROVE THE QUALITY ON RECOMMENDATIONS. LEARNING TREE (LT) IS INTRODUCED THAT CAN MODEL THE INTEREST OF LEARNERS BASED ON ATTRIBUTES OF LEARNING RESOURCES IN MULTIDIMENSIONAL SPACE USING LEARNER HISTORICAL ACCESSED RESOURCES. THEN, USING A NEW SIMILARITY MEASURE BETWEEN LEARNERS, RECOMMENDATIONS ARE GENERATED. THE EXPERIMENTAL RESULTS SHOW THAT OUR PROPOSED METHOD OUTPERFORMS CURRENT ALGORITHMS AND ALLEVIATES PROBLEMS SUCH AS COLD-START AND SPARSITY.

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APA: Copy

SALEHI, MOJTABA, & NAKHAI KAMALABADI, ISA. (2014). ATTRIBUTE-BASED RECOMMENDER SYSTEM FOR LEARNING RESOURCE BY LEARNER PREFERENCE TREE. INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE). SID. https://sid.ir/paper/926280/en

Vancouver: Copy

SALEHI MOJTABA, NAKHAI KAMALABADI ISA. ATTRIBUTE-BASED RECOMMENDER SYSTEM FOR LEARNING RESOURCE BY LEARNER PREFERENCE TREE. 2014. Available from: https://sid.ir/paper/926280/en

IEEE: Copy

MOJTABA SALEHI, and ISA NAKHAI KAMALABADI, “ATTRIBUTE-BASED RECOMMENDER SYSTEM FOR LEARNING RESOURCE BY LEARNER PREFERENCE TREE,” presented at the INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE). 2014, [Online]. Available: https://sid.ir/paper/926280/en

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