Analyses of Algorithms and Complexity for Secure Association Rule Mining of Distributed Level Hierarchy in Web
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Abstract
WWW (World Wide Web) has revolutionized the way in which people interact, carry out their works and gather information. It has proved itself to be a useful interface for its users to carry out such activities with ease. With hundreds of millions of people around the world using it a huge pile of data are collected every day. These data carries interesting insights on the way people interact with it. Web Mining is the process of using various data mining techniques to analyze and discover patterns from the data. The Web mostly contains semi-structured information. It is, however, not easy to search and extract structural data hidden in a Web page. Thus several privacy preserving techniques for association rule mining for web have also been proposed in the past few years. This paper focuses on analyses of algorithms and complexity for secure association rule mining of distributed level hierarchy in web. We also have shown that algorithm’s pseudocode for easily analyzing its complexity.
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Keywords - Vertical Partition, Privacy Preserving, Complexity, Pseudocode of Association Rule Mining
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