Algorithm Research & Explore
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1303-1305,1316

Binomial matrix factorization with rating drift for recommender systems

Zhang Xiaohong
Zhang Qizhi
Zhou Yali
School of Automation, Beijing Information Science & Technology University, Beijing 100192, China

Abstract

Based on matrix factorization techniques, this paper implemented a modified binomial matrix decomposition algorithm in order to solve the recommender system's rating prediction problem. It supposed that the user's rating of the item was based on the binomial distribution. There were differences in the user's rating habits, popularity of the items, it would result in an offset in the user-item scoring matrix. This paper used the maximum a posteriori estimate to design model and optimized the model by a stochastic gradient descent algorithm. The experimental results show that the modified binomial matrix decomposition algorithm is superior to the traditional binomial matrix decomposition algorithm in terms of recommender accuracy and offline calculation time on the MovieLens 100K datasets.

Foundation Support

国家自然科学基金资助项目(11672044,11172047)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.10.0807
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 5
Section: Algorithm Research & Explore
Pages: 1303-1305,1316
Serial Number: 1001-3695(2020)05-004-1303-03

Publish History

[2020-05-05] Printed Article

Cite This Article

张笑虹, 张奇志, 周亚丽. 引入评分偏置的二项矩阵分解推荐算法 [J]. 计算机应用研究, 2020, 37 (5): 1303-1305,1316. (Zhang Xiaohong, Zhang Qizhi, Zhou Yali. Binomial matrix factorization with rating drift for recommender systems [J]. Application Research of Computers, 2020, 37 (5): 1303-1305,1316. )

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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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