Chinese text classification algorithm based on Three－way Decisions
Jin Yilin1，2*，Hu Feng1，2
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1.College of Computer Science and Technology，Chongqing University of Posts and Telecommunications，Chongqing，400065，China；
2．Chongqing Key Laboratory of Computational Intelligence，Chongqing，400065，China
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Published
2018-04-30
Abstract
With the continuous development of information technology，more and more information has emerged. How to obtain the most valuable information quickly and effectively has become a hot spot of attention. As a branch of natural language processing，Chinese text classification can effectively help users to quickly get the information they need in massive information by summarizing information into a known topic category. With the hot of machine learning and artificial intelligence，people are more inclined to let the machine complete this tedious process to improve the accuracy of classification and the speed of retrieval. At present，there is a great shortage of Chinese text categorization，which is mainly reflected in the sparse and high dimension of the feature extraction，and cannot effectively and comprehensively represent the text of category，resulting in unsatisfactory classification results. With the introduction of the Three－way Decisions frameworks，more and more scholars have tried to apply it to various applications. This proves that the framework reduces the loss of error decision by converting the traditional two decision－making methods into three decision－making methods. Based on this theoretical framework，this paper improves the traditional feature selection algorithm for the purpose of efficiently extracting text category features，and proposes a Three－way Decision feature selection algorithm. In order to reduce the number of feature words and improve the representativeness of feature words，we combines unsupervised and supervised feature extraction algorithms with a double evaluation function to evaluate a more comprehensive feature. Finally，through the experiments on Fudan University corpus，the results show that the proposed Three－way Decision feature selection algorithm has certain advantages compared with the traditional feature selection algorithms，and in comparison with the feature selection algorithms proposed by many scholars in the last three years，our algorithm has obvious advantage in low dimension feature space. In summary，the proposed algorithm can not only effectively reduce the number of feature words and compress feature space，but also effectively improve the accuracy of Chinese text classification.
Jin Yilin1，2*，Hu Feng1，2.
Chinese text classification algorithm based on Three－way Decisions[J]. Journal of Nanjing University(Natural Sciences), 2018, 54(4): 794
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