TitlePrivacy-Preserving Collaborative Sequential Pattern Mining
Publication TypeConference Paper
Year of Publication2004
AuthorsZhan, Z., and LW. Chang
Conference NameWorkshop on Link Analysis, Counter-terrorism and Privacy

In this paper, we study how to conduct sequential pattern mining, which is one of the data mining computations, on private data in the following scenario: Multiple parties, each having a private data set, want to jointly conduct sequential pattern mining. Since no party wants to disclose its private data to other parties, a secure method needs to be provided to make such a computation feasible. We develop a practical solution to the above problem in this paper.

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