Algorithm Research & Explore
|
2625-2630

Study on recommendation quality evaluation based on empirical distribution and KL divergence

Zhang Wen1
Jiang Yipan1
Zhang Siguang2
Cui Yangbo1
Du Yuhang1
1. School of Economics & Management, Beijing University of Chemical Technology, Beijing 100029, China
2. Institutes of Science & Development, Chinese Academy of Sciences, Beijing 100190, China

Abstract

This paper proposed an approach called RQE-EDKL(recommendation quality evaluation based on empirical distribution and KL divergence) to evaluate the recommendation quality based on empirical distribution and KL divergence. QE-EDKL firstly made use of historical user-item data to produce the historical usage probability distribution of items at different quantities. Secondly, it calculated the KL divergence based on the distributions of the historical usage probability and the usa-ge probability of different recommendations. Thirdly, it regarded the recommendation with the minimum KL divergence as with the best quality and is recommended to the user. Experiments on TalkingData App data sets demonstrate that RQE-EDKL can effectively improve the quality of recommended results of collaborative filtering significantly on both accuracy and diversity.

Foundation Support

国家自然科学基金资助项目(61379046)
中央高校基本科研业务费(buctrc201504)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.02.0144
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 9
Section: Algorithm Research & Explore
Pages: 2625-2630
Serial Number: 1001-3695(2019)09-014-2625-06

Publish History

[2019-09-05] Printed Article

Cite This Article

张文, 姜祎盼, 张思光, 等. 基于经验分布和KL散度的协同过滤推荐质量评价研究 [J]. 计算机应用研究, 2019, 36 (9): 2625-2630. (Zhang Wen, Jiang Yipan, Zhang Siguang, et al. Study on recommendation quality evaluation based on empirical distribution and KL divergence [J]. Application Research of Computers, 2019, 36 (9): 2625-2630. )

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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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