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With the development and widely used of Internet and information technology, the Web has become one of the most important means to obtain information for people. According to the Web document classification and the theory of artificial neural network, a Web classification mining method based on wavelet neural network is presented in this paper. Moreover, we adopt a algorithm of reduce the number of the wavelet basic function by analysis the sparseness property of sample data which can optimize the wavelet network in a large extent, and the learning algorithm based on the gradient descent was used to train network. The structure of Web classification mining system based on wavelet neural network is given. With the ability of strong nonlinear function approach and pattern classification and fast convergence of wavelet neural network, the classification mining method can truly classify the web text information. The actual classification results show that this method is feasible and effective.