Lessen Database Scanning towards Hiding Sensitive Data based on Binary Search Approach

IT Skills Show & International Conference on Advancements in Computing Resources, (SSICACR-2017) 15 and 16 February 2017, Alagappa University, Karaikudi, Tamil Nadu, India. International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

Data mining is an emerging tool for extracting hidden knowledge from huge dataset. Major challenges in data mining are to identify, hidden information with minimum number of database scanning. The main objective is to develop an algorithm to find sensitive patterns such that preserving hidden information. This paper proposes an algorithm that uses pruning step and Binary Search Method for tackling the problems. The problem of association rule mining can be solved by using pruning and binary search method. This paper proposed and algorithm to integrate these two methods for eliminating weak candidate sets and avoiding unnecessary database scanning.

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Keywords

Association Rule, Apriori Algorithm, Minimum Association Rule Mining Support, Minimum Candidate Threshold.