An algorithm to improve the performance of string matching

Abstract

Approximate string matching algorithms are techniques used to find a pattern ‘P’ in a text ‘T’ partially or exactly. These techniques become very important in terms of performance and the accuracy of searching results. In this paper, we propose a general approach algorithm, called the Direct Matching Algorithm (DMA). The function of this algorithm is to perform direct access matching for the exact pattern or its similarities within a text depending on the location of a character in alphabetical order. We simulated the DMA in order to show its competence. The simulation result showed significant improvement in the exact string matching or similarity matching, and therefore extreme competence in the real applications.

Approximate pattern matching with gap constraints

“…These experiments thus verify that an instance in the present study can be transformed into many instances of [13], thereby also verifying the correctness of SONG. [3,9]t [2,5]a [4,9]g [1,8]t [2,9]a P3 g [1,9]t [1,9]a [1,9]g [1,9]t [1,9]a [1,9]g [1,9]t [1,9]a [1,9]g [1,9]t P4 g [1,5]t[0,6]a [2,7]g [3,9]t [2,5]a [4,9]g [1,8]t [2,9]a [1,9]g [1,9] …”

“…Similarly, with respect to the gap constraints, another lower bound of MinLf (n r 1 ) is r + m-1 + P mÀ2 k = 0 a k . So the min leaf with root n r 1 can be calculated according to Equation (5). When calculating the max leaf of a Single-root Nettree with root n r 1 , not only the length and gap constraints but also the length of the sequence should be considered.…”

“…Pattern matching is one of the essential problems in computer science with broad applications, such as bug detection [3], ontology matching [4], etc. Therefore, many researchers focus on improving the performance of pattern matching [5]. When wildcards (also known as 'don't care' characters) are introduced into the pattern, it becomes more practical, since these wildcards can give users more flexibility to control their queries.…”

A multi-pattern hash-binary hybrid algorithm for URL matching in the HTTP protocol

“…Due to the limitations of the classical algorithms, researchers have explored some newer multi-pattern matching algorithms. For example, He et al [ 15 ] proposed a string matching algorithm with an optimal time complexity; Hlayel and Hnaif [ 16 ] proposed a DMA algorithm to improve matching performance; Faro et al [ 17 ] proposed a fast short-form string matching algorithm, EPSM, based on the Intel SIMD Flow Instruction Extension (SSE) technique; Al-Ssulami [ 18 ] proposed an SSM algorithm based on Horspool; and Aldwairi et al [ 19 ] used the Bloom filter to improve the WM algorithm, and presented the EXHAUST algorithm, which reduced the number of searches for large hash tables. In addition, Faro et al [ 20 ] developed the string matching algorithm research framework called Smart, which implements BXS [ 21 ], BP2WW [ 22 ], KBNDM [ 23 ], SSECP [ 24 ], FSBNDM [ 25 ], BSDM [ 26 ] and other string matching algorithms.…”