Identifying relations between frequent patterns mined at two collaborative websites
by Jiahong Wang; Eiichiro Kodama; Toyoo Takata
International Journal of Space-Based and Situated Computing (IJSSC), Vol. 5, No. 4, 2015

Abstract: In modern business world, very often two companies collaborate with each other for their mutual benefit in such a way that, the one starts a transaction and processes a part of it, then the other processes the remainder. Similarly, in cloud computing, as a means to avoid leakage of secret information, a company may use two independent cloud management domains to store separate partitions of its database. For many users in such application environment, it would be beneficial and important to discover the relations between frequent patterns mined at respective site, and share the frequent pattern relation identifiers. The frequent pattern relation mining should be conducted without disclosing any other private data to each other site. This paper identifies a new data mining problem called pattern relation mining, introduces a new computing model called IF-THEN computing to capture the problem, and proposes a privacy-preserving pattern relation mining algorithm called CPRM. Extensive experiments were conducted to demonstrate the effectiveness of CPRM.

Online publication date: Wed, 16-Dec-2015

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