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PPS-POI-Rec: A Privacy Preserving Social Point-of-Interest Recommender System

  • Xiao Liu
  • An Liu
  • Guanfeng Liu
  • Zhixu Li
  • Jiajie Xu
  • Pengpeng Zhao
  • Lei Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9313)

Abstract

Point-of-Interest (POI) recommendation is an important task for location based service (LBS) providers. Social POI recommendation outperforms traditional, non-social approaches as social relations among users (a.k.a. social graph) could be used as a data source to calculate user similarities, which is generally hard to evaluate due to the lack of sufficient user check-in data. However, the social graph is typically owned by a social networking service (SNS) provider such as Facebook and should be hidden from LBS provider for obvious reasons of commercial benefits, as well as due to privacy legislation. In this paper, we present PPS-POI-Rec, a novel privacy preserving social POI recommender system that enables SNS provider and LBS provider to cooperatively recommend a set of POIs to a target user while keeping their private data secret. We will demonstrate step by step how a social POI recommendation can be jointly made by SNS provider and LBS provider, without revealing their private data to each other.

Keywords

POI recommendation social recommendation privacy preserving recommendation 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Xiao Liu
    • 1
    • 2
  • An Liu
    • 1
    • 2
  • Guanfeng Liu
    • 1
    • 2
  • Zhixu Li
    • 1
    • 2
  • Jiajie Xu
    • 1
    • 2
  • Pengpeng Zhao
    • 1
    • 2
  • Lei Zhao
    • 1
    • 2
  1. 1.School of Computer Science and TechnologySoochow UniversitySuzhouChina
  2. 2.Collaborative Innovation Center of Novel Software Technology and IndustrializationJiangsuChina

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