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» Reducing the Frequent Pattern Set
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GRC
2010
IEEE
13 years 9 months ago
Local Pattern Mining from Sequences Using Rough Set Theory
Abstract--Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns ...
Ken Kaneiwa, Yasuo Kudo
ADC
2008
Springer
156views Database» more  ADC 2008»
14 years 2 months ago
Interactive Mining of Frequent Itemsets over Arbitrary Time Intervals in a Data Stream
Mining frequent patterns in a data stream is very challenging for the high complexity of managing patterns with bounded memory against the unbounded data. While many approaches as...
Ming-Yen Lin, Sue-Chen Hsueh, Sheng-Kun Hwang
JCST
2008
119views more  JCST 2008»
13 years 7 months ago
Mining Frequent Generalized Itemsets and Generalized Association Rules Without Redundancy
This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules). These are compact ...
Daniel Kunkle, Donghui Zhang, Gene Cooperman
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
14 years 8 months ago
Efficient closed pattern mining in the presence of tough block constraints
In recent years, various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemsetbase...
Krishna Gade, Jianyong Wang, George Karypis
DMIN
2006
138views Data Mining» more  DMIN 2006»
13 years 9 months ago
Mining Complete Hybrid Sequential Patterns
We discovered that the set of frequent hybrid sequential patterns obtained by previous researches is incomplete, due to the inapplicability of the Apriori principle. We design and ...
Chichang Jou