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AICCSA
2008
IEEE
216views Hardware» more  AICCSA 2008»
13 years 5 months ago
Mining fault tolerant frequent patterns using pattern growth approach
Mining fault tolerant (FT) frequent patterns from transactional datasets are very complex than mining all frequent patterns (itemsets), in terms of both search space exploration a...
Shariq Bashir, Zahid Halim, Abdul Rauf Baig
KAIS
2008
114views more  KAIS 2008»
13 years 5 months ago
A new concise representation of frequent itemsets using generators and a positive border
A complete set of frequent itemsets can get undesirably large due to redundancy when the minimum support threshold is low or when the database is dense. Several concise representat...
Guimei Liu, Jinyan Li, Limsoon Wong
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
14 years 5 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
CORR
2008
Springer
114views Education» more  CORR 2008»
13 years 5 months ago
Temporal Support of Regular Expressions in Sequential Pattern Mining
Classic algorithms for sequential pattern discovery, return all frequent sequences present in a database. Since, in general, only a few ones are interesting from a user's poin...
Leticia I. Gómez, Bart Kuijpers, Alejandro ...
ICDE
2005
IEEE
176views Database» more  ICDE 2005»
13 years 11 months ago
LAPIN-SPAM: An Improved Algorithm for Mining Sequential Pattern
Sequence pattern mining is an important research problem because it is the basis of many other applications. Yet how to efficiently implement the mining is difficult due to the ...
Zhenglu Yang, Masaru Kitsuregawa