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Enhanced K_way Method In "APRIORI" Algorithm for Mining the Association Rules Through Embedding SQL Commands

Basel A. Dabwan1 , Mukti E. Jadhav2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-10 , Page no. 52-56, Oct-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i10.5256

Online published on Oct 31, 2019

Copyright © Basel A. Dabwan, Mukti E. Jadhav . 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: Basel A. Dabwan, Mukti E. Jadhav, “Enhanced K_way Method In "APRIORI" Algorithm for Mining the Association Rules Through Embedding SQL Commands,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.10, pp.52-56, 2019.

MLA Style Citation: Basel A. Dabwan, Mukti E. Jadhav "Enhanced K_way Method In "APRIORI" Algorithm for Mining the Association Rules Through Embedding SQL Commands." International Journal of Computer Sciences and Engineering 7.10 (2019): 52-56.

APA Style Citation: Basel A. Dabwan, Mukti E. Jadhav, (2019). Enhanced K_way Method In "APRIORI" Algorithm for Mining the Association Rules Through Embedding SQL Commands. International Journal of Computer Sciences and Engineering, 7(10), 52-56.

BibTex Style Citation:
@article{Dabwan_2019,
author = {Basel A. Dabwan, Mukti E. Jadhav},
title = {Enhanced K_way Method In "APRIORI" Algorithm for Mining the Association Rules Through Embedding SQL Commands},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2019},
volume = {7},
Issue = {10},
month = {10},
year = {2019},
issn = {2347-2693},
pages = {52-56},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4893},
doi = {https://doi.org/10.26438/ijcse/v7i10.5256}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i10.5256}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4893
TI - Enhanced K_way Method In "APRIORI" Algorithm for Mining the Association Rules Through Embedding SQL Commands
T2 - International Journal of Computer Sciences and Engineering
AU - Basel A. Dabwan, Mukti E. Jadhav
PY - 2019
DA - 2019/10/31
PB - IJCSE, Indore, INDIA
SP - 52-56
IS - 10
VL - 7
SN - 2347-2693
ER -

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Abstract

No doubt, the notable and bursting growth in data and databases has produced an imperative necessity for new mechanism and devices that can rationally and spontaneously convert the handled data into helpful and valid information and knowledge. Data mining is such a style that evolves non axiomatic, tacit, formerly anonymous, and possibly beneficiary information from data in databases. In this paper we achieved some Enhancements in K_way Method In "APRIORI" Algorithm for Mining the Association Rules Through Embedding SQL Commands.

Key-Words / Index Term

Ddata mining; association rules; relational, database; Apriori ; SQL

References

[1] R. Agrawal, T. Imielinski, A. Swami. Mining Association Rules between Sets of Items in Large Databases. In Proc. of the ACM SIGMOD Conference on Management of Data, 1993.
[2] R. Agrawal, R. Strikant. Fast Algorithms for Mining Association Rules. In Proc. of the Very Large Database (VLDB) Conference, 1994.
[3] Mirela Danubianu, Stefan Gheorghe Pentiuc, Iolanda Tobolcea. Mining Association Rules Inside a Relational Database – A Case Study. IARIA, 2011.pp14-20
[4] Cyrille Masson, Céline Robardet, Jean-François Boulicaut: Optimizing subset queries: a step towards SQL-based inductive databases for itemsets.in processing of ACM symposium of applied computing SAC 2004: 535-539
[5] Jamil, H.M. Ad hoc association rule mining as SQL3 queries. Proceedings IEEE International Conference on Data Mining, 2001, 609 – 612.
[6] Gang Fang Zu-Kuan Wei Yu-Lu Liu . An algorithm of improved association rules mining. In proceeding of International Conference on Machine Learning and Cybernetics, 2009, 133 - 137
[7] J. Han, Y. Fu, K. Koperski, W. Wang, and O. Zaiane. DMQL: A data mining query language for relational datbases.In Proc. of the 1996 SIGMOD workshop on research issues on data mining and knowledge discovery, Montreal, Canada, May 1996.
[8] Sunita Sarawagi, Shiby Thomas, Rakesh Agrawal, integrating Association rule mining with relational database systems, Proceedings of the 1998 ACM SIGMOD international conference on Management of data, Volume 27 Issue 2.
[9] D. Mirela, G.Stefan, T. PentiucIolanda. Mining Association Rules Inside a Relational Database – A Case Study. The Sixth International Multi-Conference on Computing in the Global Information Technology(ICCGI 2011). June 19-24, 2011 Luxembourg.14-19.
[10] Rao, V.V., R, “Efficient association rule mining using indexing support,” Proceedings of the International Conference on Recent Trends in Information Technology (ICRTIT), 3-5 June 2011, Chennai, Tamil Nadu. pp. 683 – 688.