Google scholar arxiv informatics ads IJAIS publications are indexed with Google Scholar, NASA ADS, Informatics et. al.

Call for Paper

-

March Edition 2022
International Journal of Applied Information Systems solicits high quality original research papers for the March 2022 Edition of the journal. The last date of research paper submission is February 15, 2022.

Mining Non-redundant Frequent Patterns in Taxonomy Datasets using Concept Lattices

R. Vijaya Prakash, A. Govardhan, Ssvn Sarma Published in Data Mining

Mining Non-redundant Frequent Patterns in Taxonomy Datasets using Concept Lattices
International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
Series Volume 3 Number 9
Authors R. Vijaya Prakash, A. Govardhan, Ssvn Sarma
10.5120/ijais12-450412
Download full text

  1. Vijaya R Prakash, A Govardhan and Ssvn Sarma. Article: Mining Non-redundant Frequent Patterns in Taxonomy Datasets using Concept Lattices. International Journal of Applied Information Systems 3(9):1-6, August 2012. BibTeX

    @article{key:article,
	author = "R. Vijaya Prakash and A. Govardhan and Ssvn Sarma",
	title = "Article: Mining Non-redundant Frequent Patterns in Taxonomy Datasets using Concept Lattices",
	journal = "International Journal of Applied Information Systems",
	year = 2012,
	volume = 3,
	number = 9,
	pages = "1-6",
	month = "August",
	note = "Published by Foundation of Computer Science, New York, USA"
}

Abstract

In general frequent itemsets are generated from large data sets by applying various association rule mining algorithms, these produce many redundant frequent itemsets. In this paper we proposed a new framework for Non-redundant frequent itemset generation using closed frequent itemsets without lose of information on Taxonomy Datasets using concept lattices.

Reference

  1. Agrawal, R. , Mannila, H. , Srikant, R. , Toivonen, H. , and Inkeri Verkamo, A. 1996. "Fast discovery of association rules. In Advances in Knowledge Discovery and Data Mining", U. Fayyad et al. (Eds. ), Menlo Park, CA: AAAI Press, pp. 307–328.
  2. Bayardo, R. J. 1998. "Efficiently mining long patterns from databases". In ACM SIGMOD Conf. Management of Data.
  3. Brin, S. , Motwani, R. , Ullman, J. , and Tsur, S. 1997. "Dynamic itemset counting and implication rules for market basket data". In ACM SIGMOD Conf. Management of Data.
  4. Lin, D. -I. and Kedem, Z. M. "Pincer-search: A new algorithm for discovering the maximum frequent set". In IEEE Transaction on Knowledge and Data Engineering, Vol 14, Issue 3, 2002
  5. Agrawal, R. , Srikant, R: "Fast Algorithms for Mining Association Rules". Proc. Of the VLDB Conference (1994) 487–489, Santiago (Chile)
  6. Savasere, A. , Omiecinski, E. , and Navathe, S. 1995. "An efficient algorithm for mining association rules in large databases". In 21st VLDB Conf.
  7. D. G. Kourie, Sergei O ,B. W. Watson ,DVD Merwe "An incremental algorithm to construct a lattice of set intersections". Science of Computer Programming, Vol 74, Issue 3,2009, P 128-142.
  8. Toivonen, H. , Klemettinen, M. , Ronkainen, P. , H¨at¨onen, K. , and Mannila, H. 1995. "Pruning and grouping discovered association rules". In MLnet Wkshp. on Statistics, Machine Learning, and Discovery in Databases.
  9. Zaki, M. J. , Hsiao, C. -J. , "Efficient algorithms for mining closed itemsets and their lattice structure", IEEE Transactions on Knowledge and Data Engineering, Volume: 17 , Issue: 4 2005 , Page(s): 462 – 478
  10. D. W. Cheung, J. Han, V. Ng and C. Y. Wong, "Maintenance of Discovered Association Rules in Large Databases, An Incremental updating Techniques" In Proc, Intl. Conf. on Data Engineering (ICDE'96), Pages 106 – 114.
  11. Yonatan Aumann, Ronen Feldman, Orly Lipshtat, "Borders: An Efficient Algorithm for Association Generation in Dynamic Databases" Journal of Intelligent Information System, 12, 61 – 73 (1999).
  12. Lei Wen, "An efficient algorithm for mining frequent closed itemset", Fifth World Congress on Intelligent Control and Automation, (WCICA 2004). Page(s): 4296 - 4299 Vol. 5
  13. Pasiquir, Bastide, Y. Stemme G, & Lakhal, "Generating a Condensed Representation for Association Rule" Journal of Intellegent system 24(1), 29-60, 2005.

Keywords

Non Redundant, Frequent Patterns, Concept Lattice, Association Rules, Itemset