Naive Bayesian classifier is a kind of effective text categorization methods,but it is hard to improve its performance by Boosting procedure because of its stability.

Compensation strategy of unseen feature words in naive Bayes text classification;

Multi-dimensional,multi-level text classification system for marine knowledge;

Subject-oriented text classification algorithm based on information retrieval;

Method of Chinese text categorization based on the word vector space model;

Effects of category distribution in a training set on text categorization;

A Chinese text categorization system based on the improved VSM;

Study of Web document classification based on best weight neural network ensembles;

Research on official documents intelligent processing system on the basis of multi-categories document classification of chinese text;

Inspired by the ideas of neural network ensembles,the author constructs a multi-BP neural network ensembles modeling for the web document classification,and elaborates the design methods and the framework of model.