Mining Negative Association Rules in Distributed Environment

Authors

  • Hetal Jadav  Research Scholar, M.E., Department of Information and Technology, Silver Oak College of Engineering and Technology, Ahmadabad, Gujarat, India
  • Kinjal Thakar  Assistant Professor Department of Information and Technology, Silver Oak College of Engineering and Technology, Ahmadabad, Gujarat, India

Keywords:

Data Mining, Distributed Database, Negative Association Rule Mining, K-Anonymity.

Abstract

In the data mining field, association rules are discovered having domain knowledge specified as a minimum support threshold. the more accurate the process of setting up minimum threshold, the more accurate we find association between data. The data may be positively or negatively relate to each other based on data values. Even though large in number, some data misses some interesting rules and the rules’ quality necessitates further analysis. As a result, we have proposed a hybrid approach based on apriori algorithm for mining frequent item sets. This algorithm will help to discover itemsets which are negatively associated with each other. These association is found on the base of properties of propositional logic, and therefore, requires no background knowledge to generate them. The experiments show that our approach is able to identify meaningful negative association rules within a reasonable execution time. This approach has a new algorithm based on modified apriori, so that users can mine the items without domain knowledge and it can mine the items efficiently when compared to association rules.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-04-30

Issue

Volume 4, Issue 4, March-April-2018

Section

Research Articles

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How to Cite

[1]
Hetal Jadav, Kinjal Thakar, " Mining Negative Association Rules in Distributed Environment , International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 4, pp.1515-1520, March-April-2018.