Automatic text categorization is an effective method to increase the efficiency and quality of information utilizing. The combination of a set of different classifiers can often achieve higher classification accuracy. The concept of full information matrix is first given, and then an integration method of multiple classifiers based on adaptive weight adjusting is presented in this paper. The classifiers and their weights are determined automatically and adaptively with this method. The effective integration of each classifier抯 result can be realized by analyzing the statistical information of the classifier on the training set. The classification performance is promoted by the improvement of the precision and the recall. The effectiveness of the method is shown by the text classification experiments on the Reuters-21578 text sets.