Title: Identifying relations between frequent patterns mined at two collaborative websites

Authors: Jiahong Wang; Eiichiro Kodama; Toyoo Takata

Addresses: Faculty of Software and Information Science, Iwate Prefectural University, 152-52 Sugo, Takizawa, Iwate 020-0193, Japan ' Faculty of Software and Information Science, Iwate Prefectural University, 152-52 Sugo, Takizawa, Iwate 020-0193, Japan ' Faculty of Software and Information Science, Iwate Prefectural University, 152-52 Sugo, Takizawa, Iwate 020-0193, Japan

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.

Keywords: cloud computing; cooperative computing; data mining; pattern relations; privacy preservation; privacy protection; pattern mining; collaborative websites; collaboration; frequent patterns.

DOI: 10.1504/IJSSC.2015.073718

International Journal of Space-Based and Situated Computing, 2015 Vol.5 No.4, pp.209 - 221

Received: 18 Mar 2015
Accepted: 07 May 2015
Published online: 16 Dec 2015 *

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