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» Mining Compressed Frequent-Pattern Sets
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KDD
2006
ACM
109views Data Mining» more  KDD 2006»
14 years 9 months ago
Extracting redundancy-aware top-k patterns
Observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. The significance...
Dong Xin, Hong Cheng, Xifeng Yan, Jiawei Han
KDD
2005
ACM
106views Data Mining» more  KDD 2005»
14 years 9 months ago
Simultaneous optimization of complex mining tasks with a knowledgeable cache
With an increasing use of data mining tools and techniques, we envision that a Knowledge Discovery and Data Mining System (KDDMS) will have to support and optimize for the followi...
Ruoming Jin, Kaushik Sinha, Gagan Agrawal
ADC
2003
Springer
182views Database» more  ADC 2003»
14 years 2 months ago
CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Yudho Giri Sucahyo, Raj P. Gopalan
CIKM
2006
Springer
14 years 25 days ago
Mining compressed commodity workflows from massive RFID data sets
Radio Frequency Identification (RFID) technology is fast becoming a prevalent tool in tracking commodities in supply chain management applications. The movement of commodities thr...
Hector Gonzalez, Jiawei Han, Xiaolei Li
JCST
2008
119views more  JCST 2008»
13 years 9 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