A Survey of Text Matching Techniques

  • A. Alqahtani College of Computer and Information Systems, Umm Al Qura University, Saudi Arabia
  • H. Alhakami College of Computer and Information Systems, Umm Al Qura University, Saudi Arabia https://orcid.org/0000-0002-4908-5573
  • T. Alsubait College of Computer and Information Systems, Umm Al Qura University, Saudi Arabia
  • A. Baz College of Computer and Information Systems, Umm Al Qura University, Saudi Arabia https://orcid.org/0000-0002-8669-6883
Volume: 11 | Issue: 1 | Pages: 6656-6661 | February 2021 | https://doi.org/10.48084/etasr.3968


Text matching is the process of identifying and locating particular text matches in raw data. Text matching is a vital component in practical applications and an essential process in several fields. Furthermore, several dynamic techniques have been introduced in this context in order to create ease in pattern generation from words. The process involves matching of text files, text mining, text clustering, association rule extraction, world cloud, natural language processing, and text similarity measures (knowledge-based, corpus-based, string-based, and hybrid similarities). The string-based approach forms the most conspicuous form of text mining applied in different cases. The survey attempted in the present study covers a new research premise that uses text-matching to solve problems. The study also summarizes different approaches that are being used in this domain.

Keywords: text mining, similarity measure, matching, clustering, natural language processing, word cloud


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