Presentation 2006-07-21
Distributed Privacy-preserving Document Clustering
Chunhua SU, Jianying ZHOU, Feng BAO, Kouichi SAKURAI,
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Abstract(in English) Many government organizations and companies want to share their documents in a similar theme to get the joint benefits. Textual document clustering is a powerful data mining technique to analyze the large amount of documents and structure large sets of text or hypertext documents. While doing the document clustering in the distributed environment, it may involve the users' privacy of their own document. In this paper, we propose a framework to do the privacy-preserving text mining among the users under the distributed environment: multiple parties. each having their private documents, want to collaboratively execute agglomerative document clustering without disclosing their private contents to any other parties.
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Keyword(in English) Documents Clustering / Privacy-preserving Data Mining / Secure Multi-party Computation
Paper # ISEC2006-56
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Committee ISEC
Conference Date 2006/7/14(1days)
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Registration To Information Security (ISEC)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Distributed Privacy-preserving Document Clustering
Sub Title (in English)
Keyword(1) Documents Clustering
Keyword(2) Privacy-preserving Data Mining
Keyword(3) Secure Multi-party Computation
1st Author's Name Chunhua SU
1st Author's Affiliation Department of Computer Science and Communication Engineering. Kyushu University()
2nd Author's Name Jianying ZHOU
2nd Author's Affiliation Institute for Infocomm Research (I^2R)
3rd Author's Name Feng BAO
3rd Author's Affiliation Institute for Infocomm Research (I^2R)
4th Author's Name Kouichi SAKURAI
4th Author's Affiliation Department of Computer Science and Communication Engineering. Kyushu University
Date 2006-07-21
Paper # ISEC2006-56
Volume (vol) vol.106
Number (no) 176
Page pp.pp.-
#Pages 8
Date of Issue