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SZ Data Mining Algorithm (DA): Suggestions for the Books

Published on None 2011 by Sangeeta Vhatkar
journal_cover_thumbnail
International Conference and Workshop on Emerging Trends in Technology
Foundation of Computer Science USA
ICWET - Number 15
None 2011
Authors: Sangeeta Vhatkar
cd30776a-01b5-4ba3-b93a-21d72f9be97e

Sangeeta Vhatkar . SZ Data Mining Algorithm (DA): Suggestions for the Books. International Conference and Workshop on Emerging Trends in Technology. ICWET, 15 (None 2011), 1-4.

@article{
author = { Sangeeta Vhatkar },
title = { SZ Data Mining Algorithm (DA): Suggestions for the Books },
journal = { International Conference and Workshop on Emerging Trends in Technology },
issue_date = { None 2011 },
volume = { ICWET },
number = { 15 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 1-4 },
numpages = 4,
url = { /proceedings/icwet/number15/2180-se577/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and Workshop on Emerging Trends in Technology
%A Sangeeta Vhatkar
%T SZ Data Mining Algorithm (DA): Suggestions for the Books
%J International Conference and Workshop on Emerging Trends in Technology
%@ 0975-8887
%V ICWET
%N 15
%P 1-4
%D 2011
%I International Journal of Computer Applications
Abstract

Data-mining Algorithms (DAs) are well-known for discovering large itemsets from mass-circulation and transactional databases. With the wide-range application of database system, a historical data is accumulated in the college library. Here, data-mining association rules are applied for discovering useful knowledge in the data analysis.

References
  1. Agrawal, T. Imielinski, and A. Swami, “Mining Association Rules Between Sets of Items in Large Databases”, In Proceedings of the ACM SIGMOD Conference on Management of data: 207-216, May 1993.
  2. AGRAWAL R, SRIKANT R. Fast algorithms for mining association rules. Proceedings of the 20th International Conference On Very Large Databases. Santiago, 1994: 487-499
  3. S.MITRA, S. K. RAL, and P.MITRA. “Data mining in soft computing framework: a survey”. In IEEE Transactions on Neural Networks, Vo1.13, No. 1, (2002).
  4. Han J., Chiang J., Chee S., et al., “DBMiner: A System for Data Mining in Relation Database and Data Warehouse,” Proceeding of CASCON’97 Meeting of Mindsm, Toronto, Canada, pp.103-107, November 1997.
  5. Park J.S., Chen M. S., Yu P. S., “Using a Hash-Based Method with Transaction Trimming and Database Scan Reduction for Mining Association Rules”, IEEE Trans. on Knowledge and Data Engineering, Vol. 9, No. 5, pp.813 - 825, September/October 1997.
  6. ZHU Qi-xiang,XU Yong,ZHANG Lin. Research on Mining Association Rule Based on Improved Apriori Algorithm. Compute Technology and Development. Vo1.16, NO.7. 2006: 102-105
  7. ZHANG You-gen,Qing-tao,SHAO Zhi-qing. An Improved Association Rule Mining Algorithm Based on Weight Function. Journal of East China University of Science and Technology (Natural Science Edition).Vol.32, No.5. 2006: 579-582.
Index Terms

Computer Science
Information Sciences

Keywords

Data mining Association rule frequent itemsets Apriori algorithm Improved Apriori algorithm