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A review for comparative text mining: From data acquisition to practical application.

Authors :
Wei, Na
Zhao, Songzheng
Liu, Jing
Wang, Shenghui
Source :
Journal of Information Science. Apr2023, p1.
Publication Year :
2023

Abstract

Social media provides customers with great opportunities to share their opinions regarding certain products and services. Comparative text, as an important expression form, deserves further exploration, since it contains considerable comparative information between different products and services. In this study, we review existing research on Comparative Text Mining (CTM) in the past 16 years. Basic concepts related to CTM are first described, and a general research framework is subsequently proposed. We then dive into each component of the research framework, ranging from data acquisition, comparative text identification (CTI), comparative relation extraction (CRE), to potential applications. In addition, we conduct extensive experimental analysis on existing methods for CTI and CRE, and clarify their limitations. Accordingly, we provide corresponding insights, and point out future research directions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01655515
Database :
Academic Search Index
Journal :
Journal of Information Science
Publication Type :
Academic Journal
Accession number :
163351897
Full Text :
https://doi.org/10.1177/01655515231165228