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Association Rule Mining

P. Saxena1 , R. Jain2

Section:Research Paper, Product Type: Journal Paper
Volume-2 , Issue-5 , Page no. 153-158, May-2014

Online published on May 31, 2014

Copyright © P. Saxena, R. Jain . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: P. Saxena, R. Jain, “Association Rule Mining,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.153-158, 2014.

MLA Style Citation: P. Saxena, R. Jain "Association Rule Mining." International Journal of Computer Sciences and Engineering 2.5 (2014): 153-158.

APA Style Citation: P. Saxena, R. Jain, (2014). Association Rule Mining. International Journal of Computer Sciences and Engineering, 2(5), 153-158.

BibTex Style Citation:
@article{Saxena_2014,
author = {P. Saxena, R. Jain},
title = {Association Rule Mining},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2014},
volume = {2},
Issue = {5},
month = {5},
year = {2014},
issn = {2347-2693},
pages = {153-158},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=178},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=178
TI - Association Rule Mining
T2 - International Journal of Computer Sciences and Engineering
AU - P. Saxena, R. Jain
PY - 2014
DA - 2014/05/31
PB - IJCSE, Indore, INDIA
SP - 153-158
IS - 5
VL - 2
SN - 2347-2693
ER -

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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.

Key-Words / Index Term

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

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
[1] I: Set of data items
[2] n: No. of data items
[3] D: Transactional database
[4] s: Support
[5] α: Confidence
[6] T: Tuples in database
[7] X,Y: Itemsets
[8] X ⇒ Y: Association rule
[9] Lk: Set of large itemsets of size `k`
[10] Li: Set of large itemsets for partition Di
[11] L: Set of large itemsets
[12] l :Large itemset