JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2017, Vol. 52 ›› Issue (1): 15-22.doi: 10.6040/j.issn.1671-9352.1.2015.118

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Information recommendation based on users interest model

YANG Zhen1,2,3, SI Shu-yong1, LI Chao-yang1   

  1. 1. College of Computer Science, Beijing University of Technology, Beijing 100124, China;
    2. Beijing Key Laboratory of Trusted Computing, Beijing 100124, China;
    3. Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems, Guilin University of Electronic Technology, Guilin 541004, Guangxi, China
  • Received:2015-11-14 Online:2017-01-20 Published:2017-01-16

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Abstract: Information recommendation technology can help users filtering out useful content from the huge amount of information on the Internet, thus attracts a wide range of researchers attention. In this paper, we proposed a collaborative recommendation algorithm based on the users interest by using latent factor model, which captured the users implicit interests by decompose the User-Behavior matrix into a product of a User-Implicit matrix and an Interest-Behavior matrix. The experimental results in the MovieLens data sets show that the implicit characteristic can reflect the users interest more precisely than explicit characteristics, as a result, improving the recommendation performance as an expectation.

Key words: information recommendation, users interest model, latent factor model, collaborative filtering, personalized recommendation

CLC Number: 

  • TP391
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