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» Mining Association Rules with Item Constraints
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PAKDD
2005
ACM
124views Data Mining» more  PAKDD 2005»
14 years 29 days ago
Finding Sporadic Rules Using Apriori-Inverse
We define sporadic rules as those with low support but high confidence: for example, a rare association of two symptoms indicating a rare disease. To find such rules using the w...
Yun Sing Koh, Nathan Rountree
GIS
2006
ACM
14 years 8 months ago
Mining frequent geographic patterns with knowledge constraints
The large amount of patterns generated by frequent pattern mining algorithms has been extensively addressed in the last few years. In geographic pattern mining, besides the large ...
Luis Otávio Alvares, Paulo Martins Engel, S...
TEC
2008
104views more  TEC 2008»
13 years 7 months ago
Genetic-Fuzzy Data Mining With Divide-and-Conquer Strategy
Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction data i...
Tzung-Pei Hong, Chun-Hao Chen, Yeong-Chyi Lee, Yu-...
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
DATAMINE
2006
130views more  DATAMINE 2006»
13 years 7 months ago
Mining Adaptive Ratio Rules from Distributed Data Sources
Different from traditional association-rule mining, a new paradigm called Ratio Rule (RR) was proposed recently. Ratio rules are aimed at capturing the quantitative association kno...
Jun Yan, Ning Liu, Qiang Yang, Benyu Zhang, QianSh...