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International audienceAs the web content extraction becomes more and more difficult, thispaper proposes a method that using Naive Bayes Model to train the blockattributes eigenvalues of web page. Firstly, this method denoising theweb page, represents it as a DOM tree and divides web page into blocks,then uses Naive Bayes Model to get the probability value of thestatistical feature about web blocks. At last, it extracts theme blocksto compose content of web page. The test shows that the algorithm couldextract content of web page accurately. The average accuracy has reachedup to 96.2%.The method has been adopted to extract content for theoff-portal search of Hunan Farmer Training Website, and the efficiencyis well

Chinese Web Content Extraction Based on Naïve Bayes Model