Enhancing collaborative filtering tag-based recommendationwith neural network model / Nurkhairizan Khairudin ... [et al.]

Social tagging becomes more significant when the use of these tags can benefit the searching and browsing capabilities. In the recommendation systems, the use of information such as tags can improve the accuracy of the traditional recommendation by considering social interests and social trusts betw...

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Bibliographic Details
Main Authors: Khairudin, Nurkhairizan (Author), Mohd Sharef, Nurfadhlina (Author), Masrom, Suraya (Author), Mustapha, Norwati (Author), Mohd Noah, Shahrul Azman (Author)
Format: Book
Published: Universiti Teknologi MARA, Perak, 2018-12.
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100 1 0 |a Khairudin, Nurkhairizan  |e author 
700 1 0 |a Mohd Sharef, Nurfadhlina  |e author 
700 1 0 |a Masrom, Suraya  |e author 
700 1 0 |a Mustapha, Norwati  |e author 
700 1 0 |a Mohd Noah, Shahrul Azman  |e author 
245 0 0 |a Enhancing collaborative filtering tag-based recommendationwith neural network model / Nurkhairizan Khairudin ... [et al.] 
260 |b Universiti Teknologi MARA, Perak,   |c 2018-12. 
500 |a https://ir.uitm.edu.my/id/eprint/39747/1/39747.pdf 
520 |a Social tagging becomes more significant when the use of these tags can benefit the searching and browsing capabilities. In the recommendation systems, the use of information such as tags can improve the accuracy of the traditional recommendation by considering social interests and social trusts between users. However, sparsity is one of the major problems in tag-based recommendation system because users do not always want to volunteer to contribute tags because it not compulsory. Therefore, this research proposes a neural network tag-based recommendation that makes used of available tags to further support relationships with properties of items and users. The evaluation experiments show that the proposed approach improves the recommendation quality. 
546 |a en 
690 |a Neural networks (Computer science) 
690 |a Algorithms 
655 7 |a Article  |2 local 
655 7 |a PeerReviewed  |2 local 
787 0 |n https://ir.uitm.edu.my/id/eprint/39747/ 
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