Abstract
For mobile Internet people’s personalized service needs, how to move from the vast number of mobile information in real time, accurate access to mobile users really interested in the content. In order to obtain more accurate mobile user’s preferences to meet the requirements of personalized services, this paper propose a new mobile user’s preference prediction method based on trust and link prediction by analyzing the mobile user behavior. Firstly, this paper propose a method to calculate the trust of mobile users by analyzing the behavior of mobile users; Then according to the similarity of the mobile user’s trust and the mobile user’s score, the approximate neighbor of the mobile user is selected; we use the link prediction method to calculate the correlation between mobile users and mobile network services and determine mobile network services that needed predict; Finally, we use this method to predict the user’s preference. The research shows that the prediction accuracy of this method is better than traditional method of Collaborative Filtering recommendation, which solves the sparsity problem to some extent.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (61472136; 61772196), the Hunan Provincial Focus Social Science Fund (2016ZBB006) and Hunan Provincial Social Science Achievement Review Committee results appraisal identification project (Xiang social assessment 2016JD05).
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Jiang, W., Xu, Y. (2018). Research on Mobile User Dynamic Trust Model Based on Mobile Agent System. In: Zu, Q., Hu, B. (eds) Human Centered Computing. HCC 2017. Lecture Notes in Computer Science(), vol 10745. Springer, Cham. https://doi.org/10.1007/978-3-319-74521-3_56
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DOI: https://doi.org/10.1007/978-3-319-74521-3_56
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