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Erschienen in:
2011 | OriginalPaper | Buchkapitel
A Model of a GEP-Based Text Clustering on Counter Propagation Networks
verfasst von : Jin’guang Luo, Chang’an Yuan, Jinkun Luo
Erschienen in: Emerging Research in Artificial Intelligence and Computational Intelligence
Verlag: Springer Berlin Heidelberg
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In this paper, we present a model of a GEP-based test clustering research on counter propagation networks. The idea of the model is that it optimize the link weight vector by using the advantage of the GEP(Gene Expression Programming, GEP) in combinatorial optimization. We investigate how the value of weight in the network affect the performance of the text clustering by comparing it to a based on genetic algorithm and SOM network and the method of the traditional CPN(Counter Propagation Networks, CPN) .Furthermore, we improve and optimize the weight in the CPN network by the method of GEP, thus raise the quality of the text clustering in the network. Finally, in this paper, we demonstrated the validity and superiority of the presented model.