Improved Approach for Exact Pattern Matching (original) (raw)

Improved Approach for Exact Pattern Matching (Bidirectional Exact Pattern Matching)

In this research we present Bidirectional exact pattern matching algorithm in detail. Bidirectional (BD) exact pattern matching (EPM) introduced a new idea to compare pattern with Selected Text Window (STW) of text string by using two pointers (right and left) simultaneously in searching phase. In preprocessing phase Bidirectional EPM algorithm improved the shift decision by comparing rightmost and mismatched character of Partial Text Window (PTW) to the left of pattern at same shift length. The time complexity of preprocessing phase of BD exact pattern matching is O(m) and searching phase takes O(mn/2). The proposed Bidirectional EPM algorithm is effective than the number of existing algorithms in many cases.

Improved-Bidirectional Exact Pattern Matching

In this research, we present an improved version of Bidirectional (BD) exact pattern matching (EPM) algorithm to solve the problem of exact pattern matching. Improved-Bidirectional (IBD) exact pattern matching algorithm introduced a new idea of scanning partial text window (PTW) as well with the pattern to take decision of moving pattern to the right of partial text window. IBD algorithm compares the characters of pattern to selected text window (STW) from both sides simultaneously as BD. The time complexity of preprocessing phase of IBD algorithm is O(2m) and searching phase takes O(mn/2).

Fastest Approach to Exact Pattern Matching

This research, presents an improved version of Bidirectional (BD) [20] algorithm to solve the problem of exact pattern matching. Fastest-Bidirectional (FBD) exact pattern matching algorithm introduced a new idea of scanning partial text window (PTW) as well with the pattern by taking Berry-Ravindran (BR) consecutive characters to take decision of moving pattern to the right of PTW. FBD algorithm compares the characters of pattern to selected text window from both sides simultaneously as BD. The time complexity of preprocessing phase of FBD algorithm is O(m+ |∑|) and searching phase takes O(mn/2).

Improved Text Scanning Approach for Exact String Matching

Exact String matching is an important subject in the domain of text processing and an essential component in practical applications of computer system. In this research we proposed a new algorithm to solve the problem of exact string matching by scanning text string for last and first characters of pattern in its preprocessing phase. In matching phase of TSPLFC (Test Scanning for Pattern Last and First Character) compares pattern with text window from both directions simultaneously. Experimental results verify that TSPLFC is efficient than number of existing algorithms and take its time complexity is O(km) in average case and O(1) in best case.

Enhanced Two Sliding Windows Algorithm For Pattern Matching (ETSW)

Journal of …, 2012

In this paper, we propose a string matching algorithm-Enhanced Two Sliding Windows (ETSW), which made an improvement on the Two Sliding Windows algorithm (TSW). The TSW algorithm scans the text from both sides simultaneously using two sliding windows. The ETSW algorithm enhances the TSW's process by utilizing the idea of the two sliding windows and focusing on making comparisons with the pattern from both sides simultaneously. The comparisons done between the text and the pattern are done from both sides in parallel. The experimental results show that the ETSW algorithm has enhanced the process of pattern matching by reducing the number of comparisons performed. The best time case is calculated and found to be while the average case time complexity , where m is the pattern length and n in the text length.

A Family of Exact Pattern Matching Algorithms with Multiple Adjacent Search Windows

2017

A new family of comparison-based exact pattern matching algorithms is presented. They utilize the multi-dimensional arrays in order to process more than one adjacent search window in each iteration of the search loop. This approach leads to a lower average computing time by the cost of space. However, the excessive space consumption can be avoided due to a special technique of replacing a multi-dimensional array with a series of one-dimensional arrays of pointers. The algorithms of this family perform well for short or middle-size patterns, when the shift of a search window by several lengths at once is quite probable. Our algorithms outperform all other known algorithms for some values of pattern length on English text, genomic sequence and a random text over an alphabet of size 8 or 32.

A family of fast exact pattern matching algorithms

ArXiv, 2016

A family of comparison-based exact pattern matching algorithms is described. They utilize multi-dimensional arrays in order to process more than one adjacent text window in each iteration of the search cycle. This approach leads to a lower average time complexity by the cost of space. The algorithms of this family perform well for short patterns and middle size alphabets. In such case the shift of the window by several pattern lengths at once is quite probable, which is the main factor of algorithm success. Our algorithms outperform the Boyer-Moore-Horspool algorithm, either in the original version or with Sunday's Quick search modification, in a wide area of pattern length - alphabet size plane. In some subareas the proposed algorithms are the fastest among all known exact pattern matching algorithms. Namely, they perform best when alphabet size is about 30-40 and pattern length is about 4-10. Such parameters are typical for search in natural language text databases.

COMPARATIVE ANALYSIS ON EFFICIENCY OF SINGLE STRING PATTERN MATCHING ALGORITHMS

Abstract-Data is stored in different forms but, text remains the main form of exchanging information. The manipulation of text involves several problems among which pattern matching is one of them.Pattern-matching is routinely used in various computer applications, like editors, retrieval of information etc. Pattern-matching algorithm matches the pattern exactly or approximately within the text. This paper presents the Comparative Analysis of various Pattern String matching algorithms. The highly efficient algorithms like The Brute Force Algorithm, The Karp-Rabin Algorithm, and The Boyer Moore Algorithm are used for exact or approximate patternmatching on diverse systems. After performing a detailed study on the above mentioned algorithms

A Fast Pattern Matching Algorithm Using Changing Consecutive Characters

Journal of Software Engineering and Applications, 2016

Pattern matching is a very important algorithm used in many applications such as search engine and DNA analysis. They are aiming to find a pattern in a text. This paper proposes a Pattern Matching Algorithm Using Changing Consecutive Characters (PMCCC) to make the searching process of the algorithm faster. PMCCC enhances the shift process that determines how the pattern moves in case of the occurrence of the mismatch between the pattern and the text. It enhances the Berry Ravindran (BR) shift function by using m consecutive characters where m is the pattern length. The formal basis and the algorithms are presented. The experimental results show that PMCCC made enhancements in searching process by reducing the number of comparisons and the number of attempts. Comparing the results of PMCCC with other related algorithms has shown significant enhancements in average number of comparisons and average number of attempts.

A New Efficient Hybrid String Matching Algorithm to Solve the Exact String Matching Problem

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