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Web mining based on chaotic social evolutionary programming algorithm

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1 Author(s)
Xie Bin ; School of Management, Northwestern Polytechnical Univ., Xi'an 710072, P. R. China

With an aim to the fact that the K-means clustering algorithm usually ends in local optimization and is hard to harvest global optimization, a new web clustering method is presented based on the chaotic social evolutionary programming (CSEP) algorithm. This method brings up the manner of that a cognitive agent inherits a paradigm in clustering to enable the cognitive agent to acquire a chaotic mutation operator in the betrayal. As proven in the experiment, this method can not only effectively increase web clustering efficiency, but it can also practically improve the precision of web clustering.

Published in:

Journal of Systems Engineering and Electronics  (Volume:19 ,  Issue: 6 )