Association Rule Mining

Authors

  • Priyank Saxena Amity Institute of Information Technology, Amity University, Noida, India
  • Rachna Jain Amity Institute of Information Technology, Amity University, Noida, India

Keywords:

Data Mining, Association Rules, Association Rule Algorithms, Database, Data Analysis

Abstract

Today, Association Rules are considered to be one of the more studied fields under Data Mining. It recently has come under a lot of notice by the data base warehouses. Its main use is to extract interesting associations, co-relations and frequent patterns among the groups of items recorded of the transactional databases or some different form of data storages. In this paper, a categorization and comparison of the different association rule algorithms that are present today is provided.

References

Agrwl93] RakeshAgrawal, Tomasz_Imielinski and Arun N. Swami, Mining_Association_RulesBetweenSets of Items in Large_Databases.

[Agrwl98] Charu C. Aggarwal and Philip_S. Yu, A New Framework for Itemset_Generation.

[Chn96] Ming-Syan Chen, Jiawei Han and Philip_S. Yu, Data Mining: An Overview from a Database_Perspective.

[Fayyd96] Usama M. Fayyad, Gregory_Piatetsky-Shapiro, and Padhraic Smyth, From Data Mining to knowledge Discovery: An Overview, Advances in Knowledge Discovery and Data Mining, pp 1-34.

[Chng96c] David Wai-Lok Cheung, Ada Wai-Chee Fu, Vincent T. Ng, and Yongjian Fu, Efficient Mining of Association_Rules in Distributed_Databases, Vol. 8, No. 6, pp. 911-922.

NOTATIONS

I: Set of data items

n: No. of data items

D: Transactional database

s: Support

α: Confidence

T: Tuples in database

X,Y: Itemsets

X ⇒ Y: Association rule

Lk: Set of large itemsets of size `k`

Li: Set of large itemsets for partition Di

L: Set of large itemsets

l :Large itemset

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Published

2014-05-31

How to Cite

[1]
P. Saxena and R. Jain, “Association Rule Mining”, Int. J. Comp. Sci. Eng., vol. 2, no. 5, pp. 153–158, May 2014.

Issue

Vol. 2 No. 5 (2014): IJCSE May Edition

Section

Review Article

License

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