Two-party privacy-preserving agglomerative document clustering

Chunhua Su, Jianying Zhou, Feng Bao, Tsuyoshi Takagi, Kouichi Sakurai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)


Document clustering is a powerful data mining technique to analyze the large amount of documents and structure large sets of text or hypertext documents. Many organizations or companies want to share their documents in a similar theme to get the joint benefits. However, it also brings the problem of sensitive information leakage without consideration of privacy. In this paper, we propose a cryptography-based framework to do the privacy-preserving document clustering among the users under the distributed environment: two parties, each having his private documents, want to collaboratively execute agglomerative document clustering without disclosing their private contents.

Original languageEnglish
Title of host publicationInformation Security Practice and Experience - Third International Conference, ISPEC 2007, Proceedings
PublisherSpringer Verlag
Number of pages16
ISBN (Print)3540721592, 9783540721598
Publication statusPublished - 2007
Event3rd International Conference on Information Security Practice and Experience, ISPEC 2007 - Hong Kong, Hong Kong
Duration: May 7 2007May 9 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4464 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other3rd International Conference on Information Security Practice and Experience, ISPEC 2007
Country/TerritoryHong Kong
CityHong Kong

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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