Providing naive Bayesian classifier-based private recommendations on partitioned data

Creative Commons License

KALELİ C., Polat H.

18th European Conference on Machine Learning (ECML 2007)/11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 2007), Warszawa, Polonya, 17 - 21 Eylül 2007, cilt.4702, ss.515-516 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 4702
  • Doi Numarası: 10.1007/978-3-540-74976-9_53
  • Basıldığı Şehir: Warszawa
  • Basıldığı Ülke: Polonya
  • Sayfa Sayıları: ss.515-516
  • Anadolu Üniversitesi Adresli: Evet

Özet

Data collected for collaborative filtering (CF) purposes might be split between various parties. Integrating such data is helpful for both e-companies and customers due to mutual advantageous. However, due to privacy reasons, data owners do not want to disclose their data. We hypothesize that if privacy measures are provided, data holders might decide to integrate their data to perform richer CF services. In this paper, we investigate how to achieve naive Bayesian classifier (NBC)-based CF tasks on partitioned data with privacy. We perform experiments on real data, analyze our outcomes, and provide some suggestions.