The Improved Hybrid Algorithm for the Atheer and Berry-Ravindran Algorithms

Exact string matching is one of the critical issues in the field of computer science. This study proposed a hybrid string matching algorithm called E- AbdulRazzaq. This algorithm used the best properties of two original algorithms; AbdulRazzaq and Berry-Ravindran Algorithms. The proposed algorithm showed an efficient performance in the number of attempts and number of character comparison when compared the original and recent to the standard algorithms. The proposed algorithm was applied in several types of databases, which are DNA sequences, Protein sequences, XML structures, Pitch characters, English texts, and Source codes. The Pitch database was the best match for E-AbdulRazzaq with the number of attempts involving long and short patterns, while the DNA database was the worst match. No data is specified as the best or worst with the E-AbdulRazzaq algorithm in terms of the character comparisons. The E-AbdulRazzaq algorithms ranked first in most databases when using short and long patterns, in terms of number of attempts and character comparisons.

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Efficient String Matching Algorithm for Searching Large DNA and Binary Texts

Data Analytics in Medicine ◽

10.4018/978-1-7998-1204-3.ch016 ◽

2020 ◽

pp. 298-324

Author(s):

Abdulrakeeb M. Al-Ssulami ◽

Hassan I. Mathkour ◽

Mohammed Amer Arafah

Keyword(s):

Intrusion Detection ◽

Hybrid Algorithm ◽

Binary Data ◽

String Matching ◽

The Other ◽

Intrusion Detection Systems ◽

Average Case ◽

Matching Algorithm ◽

Detection Systems ◽

Maximal Shift

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.

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Efficient String Matching Algorithm for Searching Large DNA and Binary Texts

International Journal on Semantic Web and Information Systems ◽

10.4018/ijswis.2017100110 ◽

2017 ◽

Vol 13 (4) ◽

pp. 198-220

Author(s):

Abdulrakeeb M. Al-Ssulami ◽

Hassan Mathkour ◽

Mohammed Amer Arafah

Keyword(s):

Intrusion Detection ◽

Hybrid Algorithm ◽

Binary Data ◽

String Matching ◽

The Other ◽

Intrusion Detection Systems ◽

Average Case ◽

Matching Algorithm ◽

Detection Systems ◽

Maximal Shift

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.

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Efficient String Matching Algorithm for Intrusion Detection

INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND SCIENCES ◽

10.26472/ijces.v1i1.17 ◽

2015 ◽

Vol 1 (1) ◽

pp. 18 ◽

Cited By ~ 1

Author(s):

Bhargavi Patel

Keyword(s):

Intrusion Detection ◽

String Matching ◽

Matching Algorithm

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Contribution to Semantic Analysis of Arabic Language

Advances in Artificial Intelligence ◽

10.1155/2012/620461 ◽

2012 ◽

Vol 2012 ◽

pp. 1-8 ◽

Cited By ~ 6

Author(s):

Anis Zouaghi ◽

Mounir Zrigui ◽

Georges Antoniadis ◽

Laroussi Merhbene

Keyword(s):

Information Retrieval ◽

Semantic Analysis ◽

String Matching ◽

Ambiguous Word ◽

Arabic Language ◽

New Approach ◽

Matching Algorithm ◽

Ambiguous Words ◽

Lesk Algorithm ◽

Context Of Use

We propose a new approach for determining the adequate sense of Arabic words. For that, we propose an algorithm based on information retrieval measures to identify the context of use that is the closest to the sentence containing the word to be disambiguated. The contexts of use represent a set of sentences that indicates a particular sense of the ambiguous word. These contexts are generated using the words that define the senses of the ambiguous words, the exact string-matching algorithm, and the corpus. We use the measures employed in the domain of information retrieval, Harman, Croft, and Okapi combined to the Lesk algorithm, to assign the correct sense of those proposed.

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