- Title
- Exact string matching algorithms : survey, issues, and future research directions
- Creator
- Hakak, Saqib; Kamsin, Amirrudin; Shivakumara, Palaiahnakote; Gilkar, Gulshan; Khan, Wazir; Imran, Muhammad
- Date
- 2019
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/183040
- Identifier
- vital:16233
- Identifier
-
https://doi.org/10.1109/ACCESS.2019.2914071
- Identifier
- ISBN:2169-3536 (ISSN)
- Abstract
- String matching has been an extensively studied research domain in the past two decades due to its various applications in the fields of text, image, signal, and speech processing. As a result, choosing an appropriate string matching algorithm for current applications and addressing challenges is difficult. Understanding different string matching approaches (such as exact string matching and approximate string matching algorithms), integrating several algorithms, and modifying algorithms to address related issues are also difficult. This paper presents a survey on single-pattern exact string matching algorithms. The main purpose of this survey is to propose new classification, identify new directions and highlight the possible challenges, current trends, and future works in the area of string matching algorithms with a core focus on exact string matching algorithms. © 2013 IEEE.
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Relation
- IEEE Access Vol. 7, no. (2019), p. 69614-69637
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright @ 2019 IEEE
- Rights
- Open Access
- Subject
- 40 Engineering; 46 Information and Computing Sciences; Boyer-Moore; Exact string matching; Knuth-Morris-Pratt; Pattern analysis; Pattern matching; Pattern recognition; Rabin-Karp; String matching
- Full Text
- Reviewed
- Funder
- This work was supported in part by the University of Malaya Research Grant (UMRG) under Project RP043A-17HNE & RP003A 14HNE, and in part by the Deanship of Scientific Research, King Saud University through research group under Grant RG-1435-051.
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