Title
Modified Guide (Lm) Algorithm For Mining Maximal High Utility Patterns From Data Streams
Abstract
High utility pattern mining is an emerging research topic in the data mining field. Unlike frequent pattern mining, high utility pattern mining deals with non-binary databases, in which the information about purchased quantities of items is maintained. Due to the non-existence of anti-monotone property among the utilities of itemsets, utility mining becomes a big challenge. Moreover, discovering useful patterns from the huge number of potential patterns is a mining bottleneck. However, the compact (Closed and Maximal) high utility pattern mining moderately lessens the number of patterns, but it does not solve it. Recently, an efficient framework called GUIDE, was proposed in the literature to address this issue. Though, GUIDE effectively reduced the number of high utility patterns, yet the quality of few mined patterns and their utilities are not exact. In view of this, we propose a modified MGUIDE(LM) algorithm to improve the quality and determine exact utilities of maximal patterns.
Year
DOI
Venue
2015
10.1080/18756891.2015.1023589
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
Keywords
Field
DocType
Maximal Patterns, Anti-monotone property, Data mining, High utility patterns, Transaction projection
Utility mining,Data mining,Bottleneck,Data stream mining,Computer science,Algorithm,Artificial intelligence,Machine learning
Journal
Volume
Issue
ISSN
8
3
1875-6891
Citations 
PageRank 
References 
3
0.37
14
Authors
2
Name
Order
Citations
PageRank
Chiranjeevi Manike130.37
H. Om29917.56