Association Rules: An Overview

Introducing an algorithm for use to hide sensitive association rules through perturb technique

Due to the rapid growth of data mining technology, obtaining private data on users through this technology becomes easier. Association Rules Mining is one of the data mining techniques to extract useful patterns in the form of association rules. One of the main problems in applying this technique on databases is the disclosure of sensitive data by endangering security and privacy. Hiding the as...

A new approach based on data envelopment analysis with double frontiers for ranking the discovered rules from data mining

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...

Mining Fuzzy Association Rules: An Overview

A Survey of Association Rules

Association rules are one of the most researched areas of data mining and have recently received much attention from the database community. They have proven to be quite useful in the marketing and retail communities as well as other more diverse fields. In this paper we provide an overview of association rule research.

Algorithms for Mining Association Rules: An Overview

In this paper, we provide the basic concepts about association rule mining and compared existing algorithms for association rule mining techniques. Of course, a single article cannot describe all the algorithms in detailed, yet we tried to cover the major theoretical issues, which can help the researcher in their researches. KeywordsAssociation rules, algorithm, itemsets, database.