Automatic construction of classification dimensions by clustering texts based on common words

doi:10.1016/j.eswa.2023.122292

	Automatic construction of classification dimensions by clustering texts based on common words
	Ma, Bing 1,2; Zhuge, Hai 3
	2024-03-15
发表期刊	EXPERT SYSTEMS WITH APPLICATIONS
ISSN	0957-4174
卷号	238 页码:14
摘要	A way to efficiently manage large sets of texts is to construct multiple dimensions on texts and manage the texts from the dimensions. The key problem is to use a suitable representation model of text to classify texts into class trees representing dimensions. Traditional vector-based distance definitions are unsuitable to restrict the semantic relations between texts and measure the similarity of a set of more than two texts. Frequently occurred common words within a set of texts represent the texts but traditional frequent-term-set based text clustering approaches and the topic model are unsuitable for generating class trees on texts. This paper proposes an approach to using common words to represent texts and measuring the similarity of a class of texts by calculating the sum of the weights of common words of the class that indicate the common semantics of these texts. The idea is in line with the characteristics of human classification of texts. A bottom-up text clustering approach is proposed to construct class trees of texts. The common words of each class on the class trees are used as the label of the class to indicate the common semantics of the class and manage the texts of the class. Therefore, the approach can be used to construct multiple classification trees on texts. The experiments for evaluating the classification accuracy and the structure of the constructed class trees show that our approach is better than other clustering algorithms. A document summarization approach based on our approach reaches a good performance.
关键词	Natural Language Processing Hierarchical Classification Dimension Text Summarization Text Clustering
DOI	10.1016/j.eswa.2023.122292
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61876048]
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS记录号	WOS:001105524300001
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/38084
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhuge, Hai
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Great Bay Univ, Dongguan, Peoples R China
推荐引用方式 GB/T 7714	Ma, Bing,Zhuge, Hai. Automatic construction of classification dimensions by clustering texts based on common words[J]. EXPERT SYSTEMS WITH APPLICATIONS,2024,238:14.
APA	Ma, Bing,&Zhuge, Hai.(2024).Automatic construction of classification dimensions by clustering texts based on common words.EXPERT SYSTEMS WITH APPLICATIONS,238,14.
MLA	Ma, Bing,et al."Automatic construction of classification dimensions by clustering texts based on common words".EXPERT SYSTEMS WITH APPLICATIONS 238(2024):14.