Secure Association Rule Mining for Distributed Level Hierarchy in Web
Journal Title: International Journal on Computer Science and Engineering - Year 2011, Vol 3, Issue 6
Abstract
Data mining technology can analyze massive data and it play very important role in many domains, if it used improperly it can also cause some new problem of information security. Thus several privacy preserving techniques for association rule mining have also been proposed in the past few years. Various algorithms have been developed for centralized data, while others refer to distributed data scenario. Distributed data Scenarios can also be classified as heterogeneous distributed data and homogenous distributed data and we identify that distributed data could be partitioned as horizontal partition (a.k.a. homogeneous distribution) and vertical partition (a.k.a. heterogeneous distribution). In this paper, we propose an algorithm for secure association rule mining for vertical partition.
Authors and Affiliations
Gulshan Shrivastava, , Dr. Vishal Bhatnagar
Keywords
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