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- W2249429466 abstract "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. k-anonymization is a standard method for guaranteeing personal privacy, in which data records are summarized so that any record is indistinguishable from at least (k – 1) other records. This study compares several clustering-based k-anonymization models in the context of collaborative filtering application." @default.
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- W2249429466 date "2012-01-01" @default.
- W2249429466 modified "2023-10-16" @default.
- W2249429466 title "A Study on Privacy Preserving Collaborative Filtering with Data Anonymization by Clustering" @default.
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- W2249429466 doi "https://doi.org/10.1007/978-3-642-29934-6_5" @default.
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