On Obtaining the Boyer-Moore String-Matching Algorithm by Partial Evaluation

Danvy, Olivier; Rohde, Henning Korsholm

doi:10.7146/brics.v12i29.21896

Cited by 3 publications

(6 citation statements)

References 8 publications

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“…The right-to-left scan, the bmBc shift rule, and the bmGs shift rule are three ingenious concepts used by the Boyer-Moore algorithm. [25][26][27] Together, these approaches result in a method that, for suitably big alphabets and extensive patterns, often runs in "sublinear" time. This approach use the bmBc and bmGs tables to compute the amount of moves necessary to slide the window over the text, ensuring that no match is overlooked.…”

Section: 11mentioning

confidence: 99%

“…The Shift-Or method 10,24,26,39,40 works on the principle of representing the search state as a number, with each search attempt doing a small number of arithmetic and logical operations. When the pattern length is smaller than the memory-word size of the machine, the Shift-Or method can be efficient by leveraging bitwise techniques.…”

Section: Shift-or Algorithmmentioning

confidence: 99%

“…The Karp-Rabin algorithm Karp and Rabin 6,10,26,28,41 propose a quick randomized pattern matching strategy that just checks if the text window is similar to the pattern using the hashing function since hashing can provide a simple solution to avoiding a quadratic amount of character comparisons. As a result, the algorithm may assess the similarities without examining whether the pattern exists at each location in the text.…”

Section: 17mentioning

confidence: 99%

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A survey on improving pattern matching algorithms for biological sequences

Hamed

Ibrahim

El‐Hafeez

2022

Concurrency and Computation

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Summary Pattern matching is a highly useful procedure in several stages of the computational pipelines. Furthermore, some research trends in this research domain contributed to growing biological databases and updated them throughout time. This article proposes an comparison and analysis of different algorithms for match equivalent pattern matching like complexity, efficiency, and techniques. Which algorithm is best for which DNA sequence and why? This describes the different algorithms for various activities that include pattern matching as an important aspect of functionality. This article shows that BM, Horspool, ZT, QS, FS, Smith, and SSABS methods employ the bad character preprocessing function. In addition, BM, SSABS, TVSBS, and BRFS methods are using two approaches in the preprocessing stage, which decreases the preprocessing time. Furthermore, KR, QS, SSABS, BRFS, and Shift‐Or are not recommended for the long pattern, whereas ZT, FS, d‐BM, Raita, and Smith are not recommended for the short pattern. This is because they are time‐consuming and certain algorithms, such as ZT and DCPM, use a lot of time and space during the matching and search process, while others, such as d‐BM and TSW, save space and time. Although DCPM, BRFS, and QS are quicker than other algorithms, FLPM, PAPM, and LFPM rank highest in terms of complexity time.

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Section: 11mentioning

confidence: 99%

Section: Shift-or Algorithmmentioning

confidence: 99%

Section: 17mentioning

confidence: 99%

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A survey on improving pattern matching algorithms for biological sequences

Hamed

Ibrahim

El‐Hafeez

2022

Concurrency and Computation

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“…Boyer-Moore algorithm is an algorithm used for string searching [12][13][14][15][16][17][18][19][20]. In conducting string searching, the Boyer-Moore algorithm is highly accurate.…”

Section: Ambiguous Word Search Using Boyer-moorementioning

confidence: 99%

Detecting Indonesian ambiguous sentences using Boyer-Moore algorithm

et al. 2020

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Ambiguous sentences are divided into 3 types namely phonetic, lexical, and grammatical. This study focuses on grammatical ambiguous sentences, grammatical ambiguous sentences are ambiguities that occur due to incorrect grammar, but this ambiguity will disappear once it is used within a sentence. Ambiguous sentences become a big problem when they are processed by a computer. In order for the computer to interpret ambiguous words correctly, this study seeks to develop detection of Indonesian ammbiguous sentences using Boyer Moore algorithm. This algorithm matches ambiguous sentences that are inserted as input with the data set. Then the sentence is being detected whether it contains ambiguous sentences, by calculating the percentage of similarity using cosine similarity method. Cosine similarity system is able to find out the meaning of the sentence. In the data set, the number of ambiguous sentences that can be collected is 50 words. The 50 words consist of ambiguous words data, ambiguous sentences, and ambiguous sentence meanings. This system trial was carried out for 200 times and the accuracy level was 0.935, precision was 0.9320, and Recall was 0.8. While the F-Measure was 0.8061. While the speed for word search 0.003275 seconds

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“…There are a number of tools available to delete the duplicate files in the system. The main disadvantage of these tools is that they only help to delete the files with similar categories (doc to doc, pdf to pdf, txt to txt, xls to xls).In file comparison, string searching algorithms are used and it tries to find a position where one or more than a few strings (also called patterns) are found within a string or text [2] [16].…”

Section: Introductionmentioning

confidence: 99%

An Efficient String Matching Technique for Desktop Search to Detect Duplicate Files

Vijayarani¹,

Muthulakshmi²

2017

IJITCS

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Information retrieval is used to identify the relevant documents in a document collection, which is matching a user"s query. It also refers to the automatic retrieval of documents from the large document corpus. The most important application of information retrieval system is search engine like Google, which identify those documents on the World Wide Web that are relevant to user queries. In most situations, users may download the files that are already downloaded and stored in their computer. Then, there is a chance of multiple copies of the files that are already stored in different drives and folders on the system, which in turn reduces the performance of the system and these files occupy a lot of memory space. Analyzing the contents of the file and finding their similarity is one of the major problems in text mining and information retrieval. The main objective of this research work is to analyze the file contents and deletes the duplicate files in the system. In order to perform this task, this research work proposes a new tool named Duplicate File Detector Tool i.e. DFDT. DFDT helps the user to search and delete duplicate files in the system at a minimum time. It also helps to delete the duplicate files not only with the same file category, but also with different file categories. Boyer Moore Horspool and Knuth Morris Pratt string searching algorithms are existing algorithms and these algorithms are used to compare the file contents for finding their similarity. This work also proposes a new string matching algorithm named as W2COM (Word to Word COMparison). From the experimental results it is observed that the newly proposed W2COM string matching algorithm performance is better than Boyer Moore Horspool and Knuth Morris Pratt algorithms.

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On Obtaining the Boyer-Moore String-Matching Algorithm by Partial Evaluation

Cited by 3 publications

References 8 publications

A survey on improving pattern matching algorithms for biological sequences

A survey on improving pattern matching algorithms for biological sequences

Detecting Indonesian ambiguous sentences using Boyer-Moore algorithm

An Efficient String Matching Technique for Desktop Search to Detect Duplicate Files

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