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Web Log Mining Based On Fuzzy Immunity Clonal Selection Neural Network

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1 Author(s)
Zhenguo Chen ; North China Inst. of Sci. & Technol., Beijing

Web log mining is an important application of data mining and has been widely explored. In this paper, we propose a novel fuzzy immunity clonal selection neural network (FICSNN) algorithm and apply the fuzzy immunity clonal selection neural network to the process of mining web log. The rule set which is extracted from the web log by fuzzy immunity clonal selection neural network is viewed as predictive criterion. To evaluate our method, a real dataset is selected as our experiment data. The experiment result has shown that our algorithm can obtain the better performance.

Published in:

Service Systems and Service Management, 2007 International Conference on

Date of Conference:

9-11 June 2007