Arbitrarily distributed data-based recommendations with privacy

Yakut I., Polat H.

DATA & KNOWLEDGE ENGINEERING, cilt.72, ss.239-256, 2012 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 72
  • Basım Tarihi: 2012
  • Doi Numarası: 10.1016/j.datak.2011.11.002
  • Dergi Adı: DATA & KNOWLEDGE ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.239-256
  • Anahtar Kelimeler: Privacy, Data mining, Arbitrarily distributed data, Collaborative filtering, Accuracy, ASSOCIATION RULES
  • Anadolu Üniversitesi Adresli: Evet

Özet

Collaborative filtering (CF) systems use customers' preferences about various products to offer recommendations. Providing accurate and reliable predictions is vital for both e-commerce companies and their customers. To offer such referrals, CF systems should have sufficient data. When data collected for CF purposes held by a central server, it is an easy task to provide recommendations. However, customers' preferences represented as ratings might be partitioned between two vendors. To supply trustworthy and correct predictions, such companies might desire to collaborate. Due to privacy concerns, financial fears, and legal issues; however, the parties may not want to disclose their data to each other.