Presentation | 2012-07-30 A Comparison of Clustering Methods in Privacy Preserving Collaborative Filtering Yui MATSUMOTO, Katsuhiro HONDA, Akira NOTSU, Hidetomo ICHIHASHI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | 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. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Privacy Preserving / Collaborative Filtering / Clustering Methods |
Paper # | NC2012-14 |
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Committee | NC |
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Conference Date | 2012/7/23(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A Comparison of Clustering Methods in Privacy Preserving Collaborative Filtering |
Sub Title (in English) | |
Keyword(1) | Privacy Preserving |
Keyword(2) | Collaborative Filtering |
Keyword(3) | Clustering Methods |
1st Author's Name | Yui MATSUMOTO |
1st Author's Affiliation | Graduate School of Engineering, Osaka Prefecture University() |
2nd Author's Name | Katsuhiro HONDA |
2nd Author's Affiliation | Graduate School of Engineering, Osaka Prefecture University |
3rd Author's Name | Akira NOTSU |
3rd Author's Affiliation | Graduate School of Engineering, Osaka Prefecture University |
4th Author's Name | Hidetomo ICHIHASHI |
4th Author's Affiliation | Graduate School of Engineering, Osaka Prefecture University |
Date | 2012-07-30 |
Paper # | NC2012-14 |
Volume (vol) | vol.112 |
Number (no) | 168 |
Page | pp.pp.- |
#Pages | 4 |
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