Tuesday 23rd of May 2017
 

Friend Recommendation Algorithm Based on Fragmentation of Time and Transmission of Interest


Sun Shibao, Jia Bowen, Zhang Jingshan, Zhang Yanan, Yan Xiaolong and Yin Lihang

In order to solve the problem that the recommendation quality is poor, which results from the fact that the traditional algorithm cannot dynamically generate recommendation for users and collect information, the paper put forward a friend recommendation algorithm which is based on the fragmentation of time and the transmission of interest. Firstly, the paper divides the users time into several time periods, and calculates the best push time. Secondly, the calculation method of user similarity is redefined based on the Ebbinghaus memory curve and the theory of interest transfer with taking the user browsing time as the standard. Finally, we make experiments by using Gooseeker crawler tools and MATLAB, and the results show that: the calculated similarity mean value and the stability have increased by 38.5% and 33.8%, 2% and 17.1% respectively comparing with the traditional collaborative filtering algorithm and collaborative filtering algorithm based on user similarity.

Keywords: User Similarity, Transmission of Interest, Friend Recommendation Algorithm.

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ABOUT THE AUTHORS

Sun Shibao
Born in 1970, Ph.D., professor. His research interests include intelligent information processing, digital image processing.

Jia Bowen
Born in 1992, M. S. candidate. His research interests include intelligent information processing.

Zhang Jingshan
Born in 1992, M. S. candidate. His research interests include computer network, online public opinion.

Zhang Yanan
Born in 1991, M. S. candidate. His research interests include intelligent information processing.

Yan Xiaolong
Born in 1992, M. S. candidate. His research interests include computer network, online public opinion.

Yin Lihang
Born in 1992, M. S. candidate. His research interests include computer network, online public opinion.


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