上下文感知的移动社交网络推荐算法研究<sup>*</sup>

doi:10.16451/j.cnki.issn1003-6059.201505003

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Abstract Although patterns of human activity show a large degree of freedom, they exhibit structural patterns subjected by geographic and social constraints. Aiming at various problems of personalized recommendation in mobile networks, a social network recommendation algorithm is proposed with a variety of context-aware information and combined with a series of social network analysis methods.Based on geographical location and temporal information, potential social relations among users are mined deeply to find the most similar set of users for the target user, then recommendations are carried out incorporating with social relations of the mobile users to effectively solve the problem of recommendation precision. The above study can not only help LBSN designers and developers to better understand their users and grasp their want, but also help to refine the design of their system to provide users with more appropriate applications and services.The experimental results on the real-world dataset verify the feasibility and effectiveness of the proposed algorithm, and it has higher prediction accuracy compared with existing recommendation algorithms.

Key words： Mobile Communication Mobile Social Network Context-Awareness Social Recommendation Preference Prediction

Received: 18 September 2014

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	ZHANG Zhi-Jun
	LIU Hong

Cite this article:

ZHANG Zhi-Jun,LIU Hong. Research on Context-Awareness Mobile SNS Recommendation Algorithm[J]. , 2015, 28(5): 404-410.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201505003 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2015/V28/I5/404

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