Improved collaborative filtering on recommender based systems using smoothing density-based user clustering
Recommender systems improve the user satisfaction of internet websites by offering personalized, interesting and useful recommendations to users. The most famous recommender system algorithm is collaborative filtering. However, the collaborative filtering algorithms need large amount of training dat...
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| Main Authors: | , |
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| Format: | Article |
| Published: |
Convergence Information Society
2012
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/33923/ http://www.globalcis.org/dl/citation.html?id=IJACT-1070&Search=Improved%20collaborative%20filtering%20on%20recommender&op=Title |
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| Institution: | Universiti Teknologi Malaysia |