Abstract
Point-of-interest (POI) recommendation services are growing in popularity due to the choice overloading and overwhelming information in modern life. However, frequent data leakage and hacking attacks are reducing people’s confidence. The awareness of privacy issues is multiplying among both the customers and service providers. This paper proposes a localized POI recommendation scheme combined with clustering techniques and introduces the concept of “virtual users” to protect user privacy without sacrificing too much accuracy.
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Acknowledgement
We would like to show our gratitude to the colleagues from the Department of Computer Science at the University of Kentucky and Northeastern Illinois University whose insights and expertise have inspired us. This research was supported by a Committee on Organized Research grant from Northeastern Illinois University.
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Cui, L., Wang, X., Zhang, J. (2021). Vendor-Based Privacy-Preserving POI Recommendation Network. In: Xiong, J., Wu, S., Peng, C., Tian, Y. (eds) Mobile Multimedia Communications. MobiMedia 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 394. Springer, Cham. https://doi.org/10.1007/978-3-030-89814-4_34
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DOI: https://doi.org/10.1007/978-3-030-89814-4_34
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