Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 10
2922-2925,2936

Collaborative filtering approach combined with rating overlap

Ren Lei
College of Information Mechanical & Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
DOI: 10.19734/j.issn.1001-3695.2019.06.0198

Abstract

Collaborative filtering has been the most widely employed personalized approach in recommender systems, it produces recommendations based on the user ratings observed by the host system. The issue of sparsity about the rating matrix can directly or indirectly affect the accuracy of recommendations. By analyzing the impacting ways of sparsity, it was found that the existing collaborative filtering approaches have emphasized the correlation between the rating values of items in calculating the item-based similarity, whereas the positive effect of rating overlay on improving the recommendation accuracy was not taken into consideration. By integrating the rating overlay with the classical similarity, this paper proposed an improved collaborative filtering approach. In contrast with the classical approach, the experimental results exhibit the effectiveness in promoting the prediction accuracy in the context of rating sparsity.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.06.0198
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 10
Section: Algorithm Research & Explore
Pages: 2922-2925,2936
Serial Number: 1001-3695(2020)10-008-2922-04

Publish History

[2020-10-05] Printed Article

Cite This Article

任磊. 一种结合评分重合度的协同推荐算法 [J]. 计算机应用研究, 2020, 37 (10): 2922-2925,2936. (Ren Lei. Collaborative filtering approach combined with rating overlap [J]. Application Research of Computers, 2020, 37 (10): 2922-2925,2936. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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