Providing private recommendations using naive Bayesian classifier

KALELİ C., Polat H.

5th International Atlantic Web Intelligence Conference (AWIC 2007), Fontainebleau, Fransa, 25 - 27 Haziran 2007, cilt.43, ss.168-169 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 43
  • Doi Numarası: 10.1007/978-3-540-72575-6_27
  • Basıldığı Şehir: Fontainebleau
  • Basıldığı Ülke: Fransa
  • Sayfa Sayıları: ss.168-169
  • Anadolu Üniversitesi Adresli: Evet

Özet

Today's CF systems fail to protect users' privacy. Without privacy protection, it becomes a challenge to collect sufficient and high quality data for CF. With privacy protection, users feel comfortable to provide more truthful and dependable data. In this paper, we propose to employ randomized response techniques (RRT) to protect users privacy while producing accurate referrals using naive Bayesian classifier (NBC), which is one of the most successful learning algorithms. We perform various experiments using real data sets to evaluate our privacy-preserving schemes.