Text classification method

A text classification method comprises following steps: dividing the initial training text collection into a plurality of subsets including the text in the same category based on the category, extracting the corresponding probability topic model from each subset; generating new text to balance the categories of the subsets by the corresponding probability topic model; constructing a classifier based on the balance training text collection corresponding to plural subsets; and processing text classification by the classifier. The invention can improve the classification effect of the text classification method under the condition of data skew.