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

  • Na Wei
  • , Songzheng Zhao
  • , Jing Liu*
  • , Shenghui Wang
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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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.
Original languageEnglish
Pages (from-to)1191-1203
Number of pages13
JournalJournal of information science
Volume51
Issue number5
Early online date26 Apr 2023
DOIs
Publication statusPublished - Oct 2025

Keywords

  • 2023 OA procedure

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