Network service recommendation method based on positions and trust relationship

Abstract

The invention discloses a network service recommendation method based on positions and a trust relationship. Through the method, mobile user position context information, user preferences and the trust relationship among users are fused, and personalized network service recommendation with real-time performance and interactivity is realized. According to the method, on the basis of a network service recommendation method framework based on the positions and the trust relationship, a mobile user preference similarity calculation method based on the mobile user position context information is proposed while the generality of neighbor similarity measurement is met; then a trust value calculation method is proposed in combination with basic user communication dataset information; and the mobile user preference similarity calculation method and the trust value calculation method are fused and applied to a network service recommendation process based on the mobile user positions and the trust relationship, and therefore the personalized network service recommendation method based on the mobile user positions is formed. By use of the method, the accuracy and reliability of network servicerecommendation are effectively improved, and meanwhile the problems of data sparsity and cold start possibly existing in the recommendation process are relieved.

Description

Technical field [0001] The invention relates to the technical field of collaborative filtering recommendation. Specifically, it relates to a network service recommendation method based on location and trust relationship. Background technique [0002] With the rapid development of mobile Internet, a more colorful mobile network service platform is provided for users. At the same time, service types and service contents are changing with each passing day, and limited mobile network resources and hardware resources have caused serious mobile information overload problems for mobile users. Therefore, the importance of recommendation technology in the entire Internet field has become increasingly prominent, and more and more researchers have paid more and more attention. As one of the effective means to alleviate the "information overload", the recommendation system needs to establish a binary relationship between users and items, and use the existing selection process or similar re...

AI Technical Summary

Problems solved by technology

At the same time, service types and content are changing with each passing day, and limited mobile network resources and hardware resources have brought serious mobile information overload problems to mobile users.

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