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《Intelligent Computer and Applications》 2019-04
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Research on LDA-SVM subject based on cross entropy and perplexity

XUE Jiaqi;YANG Fan;School of Information and Control Engineering,Xi'an University of Architecture and Technology;School of Science,Xi'an University of Architecture and Technology;  
At present,the classification of Chinese film and television scripts mainly relies on manual experience,which has the characteristics of high cost and lowefficiency. There is currently no research on the automatic classification of Chinese film and television scripts. This paper explores the topic extraction. The traditional topic generation model relies on the similarity of documents and paragraphs, paragraphs and sentences, sentences and words, while ignoring the similarity between text statements and statements.Firstly,the ISOMAP method is used to reduce the vector space dimension of the sample set. Secondly,the algorithm model of cross entropy combined with perplexity is proposed to determine the optimal number of topics that LDA needs to extract.Based on the above,through the script-theme method,the script is used to mine implicit subject terms of the script,while using SVMto further classify the subject words.
【CateGory Index】: TP391.1;TP181
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