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KDD
2007
ACM
184views Data Mining» more  KDD 2007»
14 years 8 months ago
Correlation search in graph databases
Correlation mining has gained great success in many application domains for its ability to capture the underlying dependency between objects. However, the research of correlation ...
Yiping Ke, James Cheng, Wilfred Ng
ICDE
2006
IEEE
222views Database» more  ICDE 2006»
14 years 9 months ago
CLAN: An Algorithm for Mining Closed Cliques from Large Dense Graph Databases
Most previously proposed frequent graph mining algorithms are intended to find the complete set of all frequent, closed subgraphs. However, in many cases only a subset of the freq...
Jianyong Wang, Zhiping Zeng, Lizhu Zhou
ML
2000
ACM
244views Machine Learning» more  ML 2000»
13 years 7 months ago
Learnable Evolution Model: Evolutionary Processes Guided by Machine Learning
A new class of evolutionary computation processes is presented, called Learnable Evolution Model or LEM. In contrast to Darwinian-type evolution that relies on mutation, recombinat...
Ryszard S. Michalski
TKDE
2008
136views more  TKDE 2008»
13 years 7 months ago
Efficient Correlation Search from Graph Databases
Correlation mining has gained great success in many application domains for its ability to capture underlying dependencies between objects. However, research on correlation mining ...
Yiping Ke, James Cheng, Wilfred Ng
GECCO
2008
Springer
115views Optimization» more  GECCO 2008»
13 years 8 months ago
A genetic programming approach to business process mining
The aim of process mining is to identify and extract process patterns from data logs to reconstruct an overall process flowchart. As business processes become more and more comple...
Chris J. Turner, Ashutosh Tiwari, Jörn Mehnen