Associative web document classification based on word mixed weight

There are two shortages when the method of classification based on association rules is applied to classify the web documents: one is that the method process the web document as a plain text, ignoring the HTML tags information of the web page; another is that either item of the association rules is only the word in the web page, without considering the weight of the word, or it quantifies the weight of the word frequency, ignoring the importance of the location of the word in the web document. Therefore, a new efficient method is proposed in the paper. It calculates the word´s mixed weight by the information of the HTML tags feature, and then mines the classification rules based on the mixed weight to classify the web pages. The result of experiment shows that the performance of this approach is better than the traditional associated classification methods.