A New Algorithm for Uncertain Problem of WEB Page Classification

For solving the uncertain problem in the process of WEB page classification, a general fusion classification model and algorithm are proposed, which based on model theory of information fusion. In the model, the hidden classification information is extracted from the WEB page, pre-processed firstly, then the processed data are input into the fusion mode, which deals with the different data with fusion algorithm, then the final classification results are concluded. An improved Bayesian network is proposed, which can not only solve the uncertain problem during the WEB page classification, but also can reduce the time complexity of the inference. The WEB data of NSTL are adopted in the experiment. The experiment proves the fusion model and fusion algorithm can solve the uncertain problem effectively