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	Experiment and Comparision on Classification of Chinese Car Reviews
	Liu, Xuedan; Wang, Yinglin
	2018
关键词	Text Classification Car Reviews Feature Selection Opinion Mining
卷号	303
DOI	10.3233/978-1-61499-900-3-810
页码	810-821
英文摘要	With the rapid development of e-commerce and online review platforms, the number of reviews of product has been multiplied, which makes it significant to mine valuable information from them for both businesses and consumers. Usually text classification methods are the main approaches to deal with this kind of problems. There are several steps in the process of text classification, and many different choices of methods or components can be selected in each step, so there are many possible combinations of schemas. However, there was lack of comparison of those different combinations in the past. In this paper, different combinations of components of text classification are constructed and evaluated. In the feature selection and weighting step, mutual information, information gain, chi-square test and TF-IDF methods are used as the alternatives. In the text classification step, four frequently used machine learning methods are selected as the components. The experiments are conducted on an annotated Chinese car reviews corpus. Results show that the combination of using chi-square test and Support Vector Machine algorithm obtain the best performance. The relationship between the performance and the number of the features is also studied, and empirical size of the corpus in this kind of task is given.
会议录出版者	IOS PRESS
会议录出版地	NIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS
语种	英语
WOS研究方向	Computer Science
WOS记录号	WOS:000467457200064
内容类型	会议论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/2982]
专题	上海财经大学
作者单位	Shanghai Univ Finance & Econ, Sch Informat Management & Engn, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Liu, Xuedan,Wang, Yinglin. Experiment and Comparision on Classification of Chinese Car Reviews[C]. 见:.

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