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Efficient String Matching Algorithm for Searching Large DNA and Binary Texts

delete2017-10-01
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A
Abdulrakeeb M. Al-Ssulami *
H
Hassan Mathkour
M
Mohammed Amer Arafah
DOI:10.4018/IJSWIS.2017100110delete
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Abstract

Abstract

En 中文
The exact string matching is essential in application areas such as Bioinformatics and Intrusion Detection Systems. Speeding-up the string matching algorithm will therefore result in accelerating the searching process in DNA and binary data. Previously, there are two types of fast algorithms exist, bit-parallel based algorithms and hashing algorithms. The bit-parallel based are efficient when dealing with patterns of short lengths, less than 64, but slow on long patterns. On the other hand, hashing algorithms have optimal sublinear average case on large alphabets and long patterns, but the efficiency not so good on small alphabet such as DNA and binary texts. In this paper, the authors present hybrid algorithm to overcome the shortcomings of those previous algorithms. The proposed algorithm is based on q-gram hashing with guaranteeing the maximal shift in advance. Experimental results on random and complete human genome confirm that the proposed algorithm is efficient on various pattern lengths and small alphabet.
Keywords:
DNA Searching
Hashing
q-Gram Practical Algorithms
String Matching
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

I
International Journal on Semantic Web and Information Systems
IF:
5.6
Papers:
471
Citations:
914

Organization

K
King Saud University
Scholars:
3.4W
Papers: 3.8W
Citations: 815
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