<span>Privacy preserving data mining has become the focus of attention government statistical agencies and database security research community who are concerned with preventing privacy disclosure during mining. Repositories large datasets include sensitive rules that need to be concealed from unauthorized access. Hence, association rule hiding emerged as one powerful techniques for knowl...

We define an optimal class association rule set to be the minimum rule set with the same predictive power of the complete class association rule set. Using this rule set instead of the complete class association rule set we can avoid redundant computation that would otherwise be required for mining predictive association rules and hence improve the efficiency of the mining process significantly...

Data envelopment analysis (DEA) is a relatively new data oriented approach to evaluate performance of a set of peer entities called decision-making units (DMUs) that convert multiple inputs into multiple outputs. Within a relative limited period, DEA has been converted into a strong quantitative and analytical tool to measure and evaluate performance. In an article written by Toloo et al. (2009...

Negative and positive association rule mining is extract needful information for large database. The generation of negative and positive rule based on interesting pattern and noninteresting pattern of database. The violation of given threshold value such as minimum support and minimum confidence generate some negative rules. The generation of association rule mining dependent some algorithm suc...

Data mining [Chen et al. 1996] is the process of extracting interesting (non-trivial, implicit, previously unknown and potentially useful) information or patterns from large information repositories such as: relational database, data warehouses, XML repository, etc. Also data mining is known as one of the core processes of Knowledge Discovery in Database (KDD). Many people take data mining as a...

Data mining is the process of extracting the previously unknown patterns from large amount of data. Privacy preserving data mining is one of the research areas in data mining. The main

Association Rule Mining (ARM) has been the area of interest for many researchers for a long time and continues to be the same. It is one of the important tasks of data mining. It aims at discovering relationships among various items in the database. The objective of this paper is to present a review on the basic concepts of ARM technique along with the recent related work that has been done in ...

As large repositories of data contain confidential rules that must be protected before published, association rule hiding becomes one of important privacy preserving data mining problems. Compared with traditional data modification methods, data reconstruction is a new promising, but not sufficiently investigated method, which is inspired by the inverse frequent set mining problem. In my PhD pe...