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Knowledge and Information Systems

, Volume 46, Issue 1, pp 33–58 | Cite as

Privacy-preserving topic model for tagging recommender systems

  • Tianqing Zhu
  • Gang LiEmail author
  • Wanlei Zhou
  • Ping Xiong
  • Cao Yuan
Regular Paper

Abstract

Tagging recommender systems provide users the freedom to explore tags and obtain recommendations. The releasing and sharing of these tagging datasets will accelerate both commercial and research work on recommender systems. However, releasing the original tagging datasets is usually confronted with serious privacy concerns, because adversaries may re-identify a user and her/his sensitive information from tagging datasets with only a little background information. Recently, several privacy techniques have been proposed to address the problem, but most of these lack a strict privacy notion, and rarely prevent individuals being re-identified from the dataset. This paper proposes a privacy- preserving tag release algorithm, PriTop. This algorithm is designed to satisfy differential privacy, a strict privacy notion with the goal of protecting users in a tagging dataset. The proposed PriTop algorithm includes three privacy-preserving operations: Private topic model generation structures the uncontrolled tags; private weight perturbation adds Laplace noise into the weights to hide the numbers of tags; while private tag selection finally finds the most suitable replacement tags for the original tags, so the exact tags can be hidden. We present extensive experimental results on four real-world datasets, Delicious, MovieLens, Last.fm and BibSonomy. While the recommendation algorithm is successful in all the cases, our results further suggest the proposed PriTop algorithm can successfully retain the utility of the datasets while preserving privacy.

Keywords

Privacy preserving Differential privacy Topic model  Recommender system Tagging system 

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Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  • Tianqing Zhu
    • 1
  • Gang Li
    • 1
    Email author
  • Wanlei Zhou
    • 1
  • Ping Xiong
    • 2
  • Cao Yuan
    • 3
  1. 1.School of Information TechnologyDeakin UniversityMelbourneAustralia
  2. 2.School of Information and Security EngineeringZhongnan University of Economics and LawWuhanChina
  3. 3.School of Information TechnologyWuhan Polytechnic UniversityWuhanChina

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