Collaborative filtering achieves personalized recommendation based on user collaboration. In this paper, how to preserve personal information in collaborative filtering is studied through several comparative experiments.
-anonymization is a standard method for guaranteeing personal privacy, in which data records are summarized so that any record is indistinguishable from at least (
– 1) other records. This study compares several clustering-based k-anonymization models in the context of collaborative filtering application.