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Classifying Web pages employing a probabilistic neural network

Classifying Web pages employing a probabilistic neural network

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The paper proposes a system capable of identifying and categorising Web pages on the basis of information filtering. The system is a three-layer probabilistic neural network (PNN) with biases and radial basis neurons in the middle layer and competitive neurons in the output layer. The domain of study involves the e-commerce area. Thus, the PNN scopes to identify e-commerce Web pages and classify them to the respective type according to a framework which describes the fundamental phases of commercial transactions in the Web. The system was tested with many types of Web pages, demonstrating the robustness of the method, since no restrictions were imposed except for the language of the content, which is English. The probabilistic classifier was used for estimating the population of specific e-commerce Web pages. Potential applications involve surveying Web activity in commercial servers, as well as Web page classification in largely expanding information areas like e-government or news and media.

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