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Discovery of Fuzzy Hierarchical Association Rules

by Reena Kumari, Jyoti Vashishtha
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 98 - Number 19
Year of Publication: 2014
Authors: Reena Kumari, Jyoti Vashishtha
10.5120/17292-7762

Reena Kumari, Jyoti Vashishtha . Discovery of Fuzzy Hierarchical Association Rules. International Journal of Computer Applications. 98, 19 ( July 2014), 20-26. DOI=10.5120/17292-7762

@article{ 10.5120/17292-7762,
author = { Reena Kumari, Jyoti Vashishtha },
title = { Discovery of Fuzzy Hierarchical Association Rules },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 98 },
number = { 19 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 20-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume98/number19/17292-7762/ },
doi = { 10.5120/17292-7762 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:26:37.860007+05:30
%A Reena Kumari
%A Jyoti Vashishtha
%T Discovery of Fuzzy Hierarchical Association Rules
%J International Journal of Computer Applications
%@ 0975-8887
%V 98
%N 19
%P 20-26
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A number of techniques have been developed to turn data into useful knowledge. Most of the algorithms in data mining find association rules among transactions using binary values and at single concept level. However it will be more exciting to discover hierarchical association rules for decision makers. In this work we have integrated association rule mining with fuzzy set theory and hierarchy. We have proposed an algorithm to discover hierarchical fuzzy association rules. We have used different minimum support and membership functions at each level of hierarchy. We have also used a predefined taxonomy for multilevel of hierarchy.

References
  1. Han J. , Kamber M. 2001. Data Mining: Concepts and Techniques. The Morgan Kaufmann Series.
  2. Agrawal R. , Imielinksi T. and A. Swami. 1993. Mining association rules between sets of items in large database, ACM SIGMOD Conference, Washington, DC, USA 207-216.
  3. Agrawal R. , Imielinksi T. and A. Swami. 1993. Database mining: a performance perspective, IEEE Trans. Knowledge Data Eng. 5 (6) 914–925.
  4. Chen M. S. , Han J. and Yu P. S. 199. , Data mining: an overview from a database perspective, IEEE Trans. Knowledge Data Eng. 8 (6) (1996) 866–883.
  5. Famili, A. , Shen, W. M. , Weber, R. ,and Simoudis, E. 1997. Data preprocessing and intelligent data analysis, Intel. Data Anal. 1 (1), 1–28.
  6. Hong T. P. , Kuo C. S. and Chi S. C. 1999. A data mining algorithm for transaction data with quantitative values, Intell. Data Anal. 3 (5). 363–376.
  7. Srikant R. and Agrawal R. 1996. Mining quantitative association rules in large relational tables, The ACM SIGMOD International Conference on Management of Data, Monreal, Canada, pp. 1–12.
  8. Zadeh L. A. 1965. Fuzzy sets, Inform. and Control 8 (3) 338–353.
  9. Kandel A. 1992. Fuzzy Expert Systems, CRC Press, Boca Raton, FL. pp. 8–19.
  10. Ha and Fu Y. 1999. Mining Multiple?Level Association Rules in Large Databases, IEEE TKDE. 1, pp. 798?805.
  11. Srikant R. and Agrawal R. 1995. Mining generalized association rules, The International Conference on Very Large Databases.
  12. Frawley, W. J. , Piatetsky-Sapiro, G. , and Matheus, C. J. 1992. Knowledge discovery in databases: An overview, International Journal of Computer Theory and Engineering, Vol. 3, No. 2,
  13. Ishibuchi, H. , Yamamoto, T. and Nakashima, T. 2001. ICDM Proceedings of the IEEE International Conference on Data Mining. pp. 241-248.
  14. Han, J. , and Fu, Y. 1995. Discovery of Multiple-level Association Rules from Large Databases.
  15. Srikant, R. , and Agrawal R. 1995. Mining Generalized Association Rules, In Proceedings of the 21st VLDB Conference, Zurich, Switzerland.
  16. Srikant R. and Agarwal R. 1996. Mining quantitative association rules in large relational tables, In Proceedings of the ACM SIGMOD International Conference on Management of Data, pp 1-12, Montreal,Quebec, Canada.
  17. Kuok, C. H. , Fu, A. , and Wong, M. H. 1998. Mining Fuzzy association rules in databases ACM SIGMOD Record, 27(1), ACM Press.
  18. Chen, G. , Wei, Q. , and Kerre E. 2000. Fuzzy Data Mining: Discovery of Fuzzy Generalized Association Rules. In Proceedings of Recent Research issues on Management of Fuzziness in Databases, Physica-verlag (Springer).
  19. Lee J. H. and Kwang H. L. 1997. An extension of association rules using fuzzy sets, presented at the IFSA'97, Prague, Czech Republic.
  20. Gautam Pratima and Pardasani K. R. . 2010. A Novel Approach For Discovery Multi Level Fuzzy Association Rule Mining, Journal of computing, volume 2, issue 3, march , ISSN 2151-9617.
  21. Koh Y. S. , Rountree N. and O'Keefe R. A 2006 Finding Non-Coincidental Sporadic Rules Using Apriori-Inverse Int'l J. Data Warehousing and Mining, vol. 2, pp. 38-54.
  22. Usha Rani, Vijaya Prakash R, and. Govardhan A. Mining Multi Level Association Rules Using Fuzzy Logic International Journal of Emerging Technology and Advanced Engineering August 2013.
  23. Ying Lin, K. , Chian B. ,Chian and T. Pei Hong, 2003. Mining Fuzzy Multiple-Level Association Rules from Quantitative Data. Applied Intelligence, 18: 79-90. Kluwer Academic Publishers. Proceedings of the 21st International Conference on VLDB, Zurich, Switzerland.
  24. Prakash, S. , Vijayakumar M. , and. Parvathi R. M. S A Novel Method of Mining Association Rule with Multi Level Concept Hierarchy, International Conference on Advanced Computer Technology (ICACT) Proceedings published by International Journal of Computer Applications (IJCA)2011.
Index Terms

Computer Science
Information Sciences

Keywords

Hierarchical Fuzzy Association Rules Taxonomy Membership function

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