Abstract
A semantic block is treated as a unit while analyzing the webpage. First, we implement the VTPS algorithm to partition a webpage into semantic blocks. Then, we propose an algorithm to extract the spatial and content features, and then construct the feature vector for each block. Based on these vectors, the SVM learning algorithm is applied to train and classify the various theme-oriented webpage blocks. At last, the classification experiments show the efficiency of this method.
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