Study on Chinese keyword extraction algorithm based on Na(l)ve Bayes model
基于朴素贝叶斯模型的中文关键词提取算法研究

A keyword extraction algorithm for Chinese documents based on Na ve Bayes model was proposed,which involved training and testing process.Parameters of the model were first obtained during training process,and then the probability of a word to be a keyword was computed based on the model during testing process.Experiment results show that the algorithm can extract more accurate keywords from a small scale document collection compared with traditional approach of if*idf.Moreover,it can flexibly extend feature items that indicate the importance of words,so it has a good scalability.