Hierarchical Classification Methods of Chinese Scientific Papers Based on Extracting Key Words

In recent years, there have been extensive studies and rapid progresses in automatic text classification, which is one of the hotspots and key techniques in the information retrieval and data mining field. Feature extraction and classification algorithm are the crucial technologies for this problem. This paper firstly proposed feature extraction algorithm based on key words, the algorithm selected key words set from special part of scientific papers, and employed mutual information to extract features. And then, proposed an improved hierarchical classification method, and realized hierarchical classification of Chinese scientific papers.