[1]XIA Rui,ZONG Chengqing.A hybrid approach to sentiment classification and feature expansion strategy[J].CAAI Transactions on Intelligent Systems,2011,6(6):483-488.
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A hybrid approach to sentiment classification and feature expansion strategy

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 6 Number of periods: 2011 6 Page number: 483-488 Column: 学术论文—自然语言处理与理解 Public date: 2011-12-25
Title:
A hybrid approach to sentiment classification and feature expansion strategy
Author(s):
XIA Rui;  ZONG Chengqing
Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
Keywords:
text classification;  sentiment classification;  hybrid model;  feature expansion
CLC:
TP391.1
DOI:
-
Abstract:
In this paper, focusing on sentiment text classification, the performance of generative and discriminative models for sentiment classification was studied, and a hybrid approach to sentiment classification was proposed. The individual generative classifier (naive Bayes，(NB) and the discriminative classifier (support vector machines，SVM) were merged into a hybrid version in a twostage process in order to overcome individual drawbacks and benefit from the merits of both systems. On the basis of the hybrid classifier, an efficient strategy of incorporating dependency features was also presented. The strategy not only increases the accuracy of the system, but also avoids the defects of increased computing volume brought by the traditional feature expansion method. Experimental results show the apparent advantages of this approach in both classification accuracy and efficiency.
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