Chinese Text Feature Classification Based on Distributed Framework

Computer & Telecommunication

2019, Vol. 1

Issue (5): 1-7 DOI:

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Chinese Text Feature Classification Based on Distributed Framework

1. Inner Mongolia University of Science and Technology; 2. Qingdao Metro Group Co., Ltd. Operating Branch

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Abstract The study uses Fudan Chinese text and Sogou Chinese document as the research object. It improves the Chinese text classification accuracy and recall rate. And it analyzes and obtains the best contribution value of the feature words. Based on naive Bayes classification method, improved TFIDF keyword extraction and weight calculation, the TNBIF model classification method is proposed and implemented on the Spark platform. The experimental results show that the Chinese text classification is applied by the TNBIF model. The accuracy is as high as 95.49%, which is 5.41% higher than the traditional text classification method and the recall rate is increased by 6.64%. This study obtains an optimal contribution of 0.95.

Key words： TNBIF model massive data set Spark feature classification parallel classification

Published: 13 August 2019

ZTFLH:

TP391.1

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	ZHANG Hui-fang ZONG Cai-le ZHANG Xiao-lin

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ZHANG Hui-fang ZONG Cai-le ZHANG Xiao-lin. Chinese Text Feature Classification Based on Distributed Framework. Computer & Telecommunication, 2019, 1(5): 1-7.

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http://www.computertelecom.com.cn/EN/ OR http://www.computertelecom.com.cn/EN/Y2019/V1/I5/1

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