AN INFORMATION DIFFLUENCE MECHANISM FOR CHINESE TEXT FILTERING

The information diffluence has an important role in improving the efficiency of text filtering, so a new mechanism for information diffluence is presented in this paper. The main idea of the mechanism is shown as follows: Based on the concept expansion for the keyword given by users, user profiles are automatically constructed into the structure of CDT （concept based decision tree）, and the mechanism for information diffluence is based on the CDT. It has the common segments shared by users, and it implements the quantitative matching between texts and user profiles based on the side similarity and the side matching ratio. Consequently, it weakens the strict Boolean constraint and overcomes the shortcoming of the vector space model which only focuses on the quantitative factors. As a result, the mechanism can express the information requirements for diverse users across the board and remarkably improve the efficiency of text filtering.