Triggering Uttermost Escalated Patterns for Refined Clustering

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-22 Number-2
Year of Publication : 2015
Authors : Garima Singh, Mrs. Suraiya Parveen (A.P)
  10.14445/22312803/IJCTT-V22P120

MLA

Garima Singh, Mrs. Suraiya Parveen (A.P) "Triggering Uttermost Escalated Patterns for Refined Clustering". International Journal of Computer Trends and Technology (IJCTT) V22(2):99-102, April 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
The clustering algorithm, so far, are inefficient in finding interested patterns as they reckon on the position of data items which results in large number of illegitimate patterns. The generated illegitimate patterns have low association between them providing knowledge which is of nominal significance to the user. The existing algorithm results in poor propensity among the data items. To perform the excerption of escalated patterns, the proposed algorithm uses a nominal threshold value as decided by the user. The escalated patterns will be excerpted using E-confidence and mining for knowledge will be applied on these patterns. The resulting data patterns have high propensity amid them. Thus providing the utmost knowledge to the user.

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Keywords
Escalated patterns, nominal threshold, illegitimate patterns, propensity.