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Volumn , Issue , 2012, Pages 195-202

BlurMe: Inferring and obfuscating user gender based on ratings

Author keywords

Privacy; Recommender systems

Indexed keywords

COLD START PROBLEMS; DESIGN TECHNIQUE;

EID: 84867394997     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2365952.2365989     Document Type: Conference Paper
Times cited : (186)

References (15)
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    • Koren, Y.1    Bell, R.2    Volinsky, C.3
  • 7
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    • A comparison of event models for Naive Bayes text classification
    • A. McCallum and K. Nigam. A comparison of event models for Naive Bayes text classification. In AAAI, 1998.
    • (1998) AAAI
    • McCallum, A.1    Nigam, K.2
  • 8
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    • Differentially private recommender systems: Building privacy into the net
    • F. McSherry and I. Mironov. Differentially private recommender systems: building privacy into the net. In KDD, 2009.
    • (2009) KDD
    • McSherry, F.1    Mironov, I.2
  • 9
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    • You are who you know: Inferring user profiles in Online Social Networks
    • A. Mislove, B. Viswanath, K. P. Gummadi, and P. Druschel. You are who you know: Inferring user profiles in Online Social Networks. In WSDM, 2010.
    • (2010) WSDM
    • Mislove, A.1    Viswanath, B.2    Gummadi, K.P.3    Druschel, P.4
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    • Inferring gender of movie reviewers: Exploiting writing style, content and metadata
    • J. Otterbacher. Inferring gender of movie reviewers: exploiting writing style, content and metadata. In CIKM, 2010.
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    • Otterbacher, J.1
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    • Relational learning via collective matrix factorization
    • A. P. Singh and G. J. Gordon. Relational learning via collective matrix factorization. In KDD, 2008.
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    • Trackmenot: Enhancing the privacy of web search
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    • Noise injection for search privacy protection
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.