Thoughts and Practice on the Education Projects of Sino-foreign Credit Mutual Recognition in Private Undergraduate Universities

International development is a challenge that each university must face.The educational mechanism of private undergraduate universities is flexible,and has certain advantages in expanding international education programs.Sino-foreign credit mutual recognition programs are more common in private undergraduate universities.With the continuous development of resources and models on international education cooperation,the forms of Sino-foreign credits mutual recognition cooperation are becoming more diversified.The rapid development of Chinese and foreign credit recognition education programs in private undergraduate universities requires scientific and advanced management concepts and support.Young private universities have short international development time and lack of experience.Therefore,relevant issues should be more researched.This paper analyzes the problems and challenges in the education mode and management of Sino-foreign credit mutual recognition projects in private undergraduate universities,and puts forward relevant countermeasures.

Feature selection algorithm for text classification based on improved mutual information

In order to solve the poor performance in text classification when using traditional formula of mutual information （MI） , a feature selection algorithm were proposed based on improved mutual information. The improved mutual information algorithm, which is on the basis of traditional improved mutual information methods that enbance the MI value of negative characteristics and feature＇ s frequency, supports the concept of concentration degree and dispersion degree. In accordance with the concept of concentration degree and dispersion degree, formulas which embody concentration degree and dispersion degree were constructed and the improved mutual information was implemented based on these. In this paper, the feature selection algorithm was applied based on improved mutual information to a text classifier based on Biomimetic Pattern Recognition and it was compared with several other feature selection methods. The experimental results showed that the improved mutu- al information feature selection method greatly enhances the performance compared with traditional mutual information feature selection methods and the performance is better than that of information gain. Through the introduction of the concept of concentration degree and dispersion degree, the improved mutual information feature selection method greatly improves the performance of text classification system.