基于两步策略的文本分类方法实验研究

Journal of Guangxi Normal University(Natural Science Edition) ›› 2011, Vol. 29 ›› Issue (4): 35-38.

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Text ClassificationBased on Experimental Study of Two-step Strategy

HE Quan-hao, FAN Xing-hua, ZHOU Peng

Institute of Computer Science and Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065,China

Received:2011-09-25 Published:2018-11-16

Abstract

Abstract: Naive Bayesian classifier is known to use two-step classification strategy to improve the efficiency of two types of Chinese text categorization.This paper tries to solve the following three questions:(1) the condition of a classifier to be fulfilled by using two-step strategy text classification,(2) the theoretical analysis of the three classifiers which can be used for two-step strategy text classification,(3) experimental results comparison ofRocchio,Naive Bayes,KNN combination used in many types of English text classification.Experimental results show that the Rocchio,NB and KNN satisfy the conditions of two-step strategy.Best performance is achieved by using KNN as the firststep classifier and NB as the second.

Key words: text categorization, two-step strategy, Rocchio, naiveBayes, KNN

CLC Number:

TP18

HE Quan-hao, FAN Xing-hua, ZHOU Peng. Text ClassificationBased on Experimental Study of Two-step Strategy[J].Journal of Guangxi Normal University(Natural Science Edition), 2011, 29(4): 35-38.

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