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» Selective association rule generation
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HICSS
2003
IEEE
116views Biometrics» more  HICSS 2003»
15 years 5 months ago
Modeling Instrumental Conditioning - The Behavioral Regulation Approach
Basically, instrumental conditioning is learning through consequences: Behavior that produces positive results (high “instrumental response”) is reinforced, and that which pro...
Jose J. Gonzalez, Agata Sawicka
HICSS
2003
IEEE
171views Biometrics» more  HICSS 2003»
15 years 5 months ago
Improving the Efficiency of Interactive Sequential Pattern Mining by Incremental Pattern Discovery
The discovery of sequential patterns, which extends beyond frequent item-set finding of association rule mining, has become a challenging task due to its complexity. Essentially, ...
Ming-Yen Lin, Suh-Yin Lee
HIPC
2003
Springer
15 years 5 months ago
Parallel and Distributed Frequent Itemset Mining on Dynamic Datasets
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...
ICDM
2002
IEEE
145views Data Mining» more  ICDM 2002»
15 years 4 months ago
Mining Top-K Frequent Closed Patterns without Minimum Support
In this paper, we propose a new mining task: mining top-k frequent closed patterns of length no less than min , where k is the desired number of frequent closed patterns to be min...
Jiawei Han, Jianyong Wang, Ying Lu, Petre Tzvetkov
HASKELL
2007
ACM
15 years 3 months ago
A type-preserving closure conversion in haskell
The use of typed intermediate languages can significantly increase the reliability of a compiler. By type-checking the code produced at each transformation stage, one can identify...
Louis-Julien Guillemette, Stefan Monnier