Open AccessA Survey of Text Matching Techniques
Author(s) -
Alaa M. Alqahtani,
Hosam Alhakami,
Tahani Alsubait,
Abdullah Baz
Publication year - 2021
Publication title -
engineering, technology and applied science research/engineering, technology and applied science research
Language(s) - English
Resource type - Journals
eISSN - 2241-4487
pISSN - 1792-8036
DOI - 10.48084/etasr.3968
Subject(s) - computer science , matching (statistics) , information retrieval , natural language processing , cluster analysis , process (computing) , context (archaeology) , string (physics) , artificial intelligence , similarity (geometry) , string searching algorithm , pattern matching , data mining , image (mathematics) , mathematics , geography , statistics , mathematical physics , operating system , archaeology
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.