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2008
IEEE

Attribute Value Taxonomy Generation through Matrix Based Adaptive Genetic Algorithm

10 years 1 months ago
Attribute Value Taxonomy Generation through Matrix Based Adaptive Genetic Algorithm
We introduce a new adaptive genetic method for AVT generation, MCM-AVT-Learner. The MCM-AVTLearner imports the mutation and crossover matrices which makes effective use of the fitness ranking and loci statistics information. The suggested method is not only parameterfree, but also capable of producing high quality AVTs. We describe experiments on several complete and missing benchmark data sets that compare the performance of AVTDTL using the reslut AVTs of the MCM-AVT-Learner and existing AVT learning algorithms. Results show that the AVTs generated by MCM-AVT-Learner are competitive with human-generated AVTs or AVTs generated by HAC-AVTLearner and GA-AVT-Learner in terms of classification accuracy and the compactness of the classifier.
Hyunsung Jo, Yong-chan Na, Byonghwa Oh, Jihoon Yan
Added 31 May 2010
Updated 31 May 2010
Type Conference
Year 2008
Where ICTAI
Authors Hyunsung Jo, Yong-chan Na, Byonghwa Oh, Jihoon Yang, Vasant Honavar
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