A New Efficient Hybrid String Matching Algorithm to Solve the Exact String Matching Problem
Sinan Sameer Mahmood Al-Dabbagh, Nawaf Hazim Barnouti
Journal of Advances in Mathematics and Computer Science · pp. 1–14 · Published 29 Dec 2016
10.9734/BJMCS/2017/30497Abstract
The string matching algorithms are considered one of the most studied in the computer science field because the fundamental role they play in many different applications such as information retrieval, editors, security applications, firewall, and biological applications. This study aims to introduce a new hybrid algorithm based on two well-known algorithms, namely, the modified Horspool and SSABS hybrid algorithms. Two factors used to analyze the proposed algorithm which is the total number of character comparisons and total number of attempts. The ABSBMH algorithm which is the name chosen for the proposed hybrid algorithm was tested on different types of standard datatype. The ABSBMH algorithm shows less number of character comparisons when compared to the results of other algorithms, while show almost no big different in the results of number of attempts this is due to the proposed hybrid algorithm preprocessing phase based on SSABS algorithm which is the same preprocessing phase of the Quick Search algorithm, so for all these reasons the results of the ABSBMH and other algorithms in terms of total number of attempts have been shown a small different, this is because it use different pattern lengths which are selected randomly from the databases. The experiential results expose that performance of the hybrid algorithm influenced by the type of the dataset used, the DNA sequence shows the worst result, while the English text datatype show the best results in terms of total number of character comparisons.
Cited by 11
Masoumeh Moeini, Hadi Shahriar Shahhoseini · 2022 27th International Computer Conference, Computer Society of Iran (CSICC) · 2022
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
11
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.