Changqin Quan, Fuji Ren, Tingting He et al. · 2008
The size and growth rate of biomedical abbreviation are increasing very fast, automatic construction of biomedical abbreviations dictionary from text helps to understand biomedical literature, and to update existing databases, ontologies, and dictionaries. This paper proposes a new method for automatic construction of biomedical abbreviations dictionary from text by combining string matching algorithm and searching algorithm. The string matching algorithm extracts abbreviations and their longforms. The searching algorithm corrects the false longforms produced by the string matching algorithm. The searching algorithm is based on the idea that readers often lookup relative articles to judge the longform of an abbreviation is correct or not. Our experiments show that the algorithm has high precision (97.5%) and recall (82.2%). And because tagged corpus is not necessary, the method has high efficiency.
Cited by 1
Adhi Kusnadi, Abraham Khrisnandi Wicaksono · Ultima Computing Jurnal Sistem Komputer · 2017
String searching is the search process by using the index to find text that can help in information retrieval systems. Continuing previous research, this study uses an algorithm Horspool and Zhu-Takaoka to find the performance of each of these algorithms in the search for a pattern in the text. So they make a useful desktop-based application to measure performance of both algorithm, particulary the time required to perform string searching process. Using the method of prototyping and Microsoft Visual Studio with C# programming language implementation. Result obtained from this application is the number of words found, and the processing time of each algorithm. From this study, the Horspool algorithm is 19,82845 percent faster in first test with the pattern "swan" in a text file 50 multiples 1000 words and 15.9442 percent in the second trial using text files 70000 words with different pattern than the number of characters Zhu algorithm -Takaoka in the process of searching string.
 Index Terms-String searching, Horspool, Zhu-Takaoka, Microsoft Visual Studio, application, processing time.
Cited by 5Open access
Robbi Rahim, Ansari Saleh Ahmar, Anak Agung Ayu Putri Ardyanti et al. · Journal of Physics Conference Series · 2017
This research shows the process of string matching using a Boyer-Moore algorithm in the form of visual simulation by doing string searching of a pattern string, the result of visualization is recognized that Boyer-Moore algorithm will compare a n string from the right and will test to n-1 String to get the appropriate character of the desired input string.
Cited by 25Open access
Hua Song · 2004
String matching algorithms are very important analyzing methods in content filtering and detection In this paper, some existing string matching algorithms are analyzed first, and then a new multi pattern string matching algorithm is presented The new algorithm adopts the BM algorithm's shift methods, uses the suffix tree algorithm to get the maximum shift value, and employs the AC algorithm's automaton in a matching string Analytical and experimental results show that the new algorithm is faster in searching large sets of patterns
Cited by 4
Yoshimasa Takabatake, Kenta Nakashima, Tetsuji Kuboyama et al. · arXiv (Cornell University) · 2016
Although several self-indexes for highly repetitive text collections exist, developing an index and search algorithm with editing operations remains a challenge. Edit distance with moves (EDM) is a string-to-string distance measure that includes substring moves in addition to ordinal editing operations to turn one string into another. Although the problem of computing EDM is intractable, it has a wide range of potential applications, especially in approximate string retrieval. Despite the importance of computing EDM, there has been no efficient method for indexing and searching large text collections based on the EDM measure. We propose the first algorithm, named string index for edit distance with moves (siEDM), for indexing and searching strings with EDM. The siEDM algorithm builds an index structure by leveraging the idea behind the edit sensitive parsing (ESP), an efficient algorithm enabling approximately computing EDM with guarantees of upper and lower bounds for the exact EDM. siEDM efficiently prunes the space for searching query strings by the proposed method, which enables fast query searches with the same guarantee as ESP. We experimentally tested the ability of siEDM to index and search strings on benchmark datasets, and we showed siEDM's efficiency.
Cited by 1Open access
Yoshimasa Takabatake, Kenta Nakashima, Tetsuji Kuboyama et al. · Algorithms · 2016
Although several self-indexes for highly repetitive text collections exist, developing an index and search algorithm with editing operations remains a challenge. Edit distance with moves (EDM) is a string-to-string distance measure that includes substring moves in addition to ordinal editing operations to turn one string into another. Although the problem of computing EDM is intractable, it has a wide range of potential applications, especially in approximate string retrieval. Despite the importance of computing EDM, there has been no efficient method for indexing and searching large text collections based on the EDM measure. We propose the first algorithm, named string index for edit distance with moves (siEDM), for indexing and searching strings with EDM. The siEDM algorithm builds an index structure by leveraging the idea behind the edit sensitive parsing (ESP), an efficient algorithm enabling approximately computing EDM with guarantees of upper and lower bounds for the exact EDM. siEDM efficiently prunes the space for searching query strings by the proposed method, which enables fast query searches with the same guarantee as ESP. We experimentally tested the ability of siEDM to index and search strings on benchmark datasets, and we showed siEDM’s efficiency.
Cited by 12Open access
2008
String matching problem has been received extensive research, most of which follow a common procedure, i.e., compare keywords with substring of text within a fixed length window, and then shift the window from left to right as far as possible. According to the way that patterns are compared with the text in the window, string matching algorithms can be categorized into three classes: prefix searching, suffix searching and factor searching. In prefix searching methods, window-shifting is accomplished through computing the longest common prefix between the text and the patterns. There are two ways to compute the length of the longest prefix. The first way is to compute the longest suffix of the text read that is also a prefix of the string, typified by the famous KMP� � Knuth-Morris-Pratt� � algorithm [2] and the Aho-Corasick algorithm[3]. The second maintain a set of prefix of keywords that are also suffix of text, and update the set at each character read. This is what the Shift-And and the Shift-Or algorithm do[4]. The suffix searching approach consists in searching backward for a suffix of the window that is also a suffix of the keyword, which features the backward searching from right to left within the window. The Boyer-Moore algorithm[5] is of this kind, and so are the Commentz-Walter algorithm [6]and the Wu-Manber algorithm[7].
Cited by 0
謝一功 · 2008
In this thesis, we discuss the exact string matching problem and approximate string matching problem. We avoid using a brute-force algorithm to solve the string matching problem. We improve the Bad Character Rule of Boyer and Moore Algorithm and compare it with the Horspool Algorithm. And we find that the improved method include the information of the Horspool Algorithm. Therefore, we combine the improved method with the Horspool Algorithm. The combinative method has a better efficiency in searching phase.
Cited by 0
Manuel Barrio, Pablo de la Fuente, Jesús Vegas · 2007
Search algorithms are considered as one of the most important parts of Information Retrieval. In this paper we show different algorithms regarding string matching and, specifically, the Shift Or algorithm. As far as efficiency is concerned, this algorithm depends on the pattern lenght which is bounded by the computer word size. Our main interest is to build a modified version that does not depend on the length of the pattern and preserves the original properties of the original one. 1 Introduction There are a lot of situations, like information retrieval, symbol manipulation, text edition, etc., that require string searching. There are several string searching problems: string matching, string distance, approximate string matching problem, etc. In this paper we are centered on string matching. The problem is usually formulated as follows: given a pattern string q, of size m, and a text string t, of size n, where m;n ? 0 and m n, find all occurrences of q within t, or the first ---...
Cited by 0
G. Arumugam · Zenodo (CERN European Organization for Nuclear Research) · 2011
The web has become a resourceful tool for almost all domains today. Search engines prominently use inverted indexing technique to locate the web pages having the users query. The performance of inverted index fundamentally depends upon the searching of keyword in the list maintained by search engine. Text matching is done with the help of string matching algorithm. It is important to any string matching algorithm to locate quickly the occurrences of the user specified pattern in large text. In this paper a new string matching algorithm for keyword searching is proposed. The proposed algorithm relies on new technique based on pattern length and FML (First-Middle-Last) character match. This proposed algorithm is analysed and implemented. The extensive testing and comparisons are done with BoyerMoore, Naïve, Improved Naïve, Horspool and Zhu Takaoka. The result shows that the proposed algorithm takes less time than other existing algorithm.
Cited by 0Open access
A.M.Suganya Arumugampillai · Zenodo (CERN European Organization for Nuclear Research) · 2026
The web has become a resourceful tool for almost all domains today. Search engines prominently use inverted indexing technique to locate the web pages having the users query. The performance of inverted index fundamentally depends upon the searching of keyword in the list maintained by search engine. Text matching is done with the help of string matching algorithm. It is important to any string matching algorithm to locate quickly the occurrences of the user specified pattern in large text. In this paper a new string matching algorithm for keyword searching is proposed. The proposed algorithm relies on new technique based on pattern length and FML (First-Middle-Last) character match. This proposed algorithm is analysed and implemented. The extensive testing and comparisons are done with BoyerMoore, Naïve, Improved Naïve, Horspool and Zhu Takaoka. The result shows that the proposed algorithm takes less time than other existing algorithm.
Cited by 0Open access
A.M.Suganya Arumugampillai · Zenodo (CERN European Organization for Nuclear Research) · 2026
The web has become a resourceful tool for almost all domains today. Search engines prominently use inverted indexing technique to locate the web pages having the users query. The performance of inverted index fundamentally depends upon the searching of keyword in the list maintained by search engine. Text matching is done with the help of string matching algorithm. It is important to any string matching algorithm to locate quickly the occurrences of the user specified pattern in large text. In this paper a new string matching algorithm for keyword searching is proposed. The proposed algorithm relies on new technique based on pattern length and FML (First-Middle-Last) character match. This proposed algorithm is analysed and implemented. The extensive testing and comparisons are done with BoyerMoore, Naïve, Improved Naïve, Horspool and Zhu Takaoka. The result shows that the proposed algorithm takes less time than other existing algorithm.
Cited by 0Open access
R Acharya, C Agarwal, Rasool et al. · Abertay Research Portal (Abertay University)
BackgroundString searching within a large corpus of data is a critical component of digital forensic (DF) analysis techniques such as file carving.The continuing increase in capacity of consumer storage devices requires similar improvements to the performance of string searching techniques employed by DF tools used to analyse forensic data.As string searching is a trivially-parallelisable problem, general purpose graphic processing unit (GPGPU) approaches are a natural fit.Currently, only some of the research in employing GPGPU programming has been transferred to the field of DF, of which, a closed-source GPGPU framework was used-Complete Unified Device Architecture (CUDA).Findings from these earlier studies have found that local storage devices from which forensic data are read present an insurmountable performance bottleneck. AimThis research hypothesises that modern storage devices no longer present a performance bottleneck to the currently used processing techniques of the field, andproposes that an open-standards GPGPU framework solution -Open Computing Language (OpenCL) -would be better suited to accelerate file carving with wider compatibility across an array of modern GPGPU hardware.This research further hypothesises that a modern multi-string searching algorithm may be better adapted to fulfil the requirements of DF investigation. MethodsThis research presents a review of existing research and tools used to perform file carving and acknowledges related work within the field.To test the hypothesis, parallel v file carving software was created using C# and OpenCL, employing both a traditional string searching algorithm and a modern multi-string searching algorithm to conduct an analysis of forensic data.A set of case studies that demonstrate and evaluate potential benefits of adopting various methods in conducting string searching on forensic data are given.This research concludes with a final case study which evaluates the performance to perform file carving with the best-proposed string searching solution and compares the result with an existing file carving tool-Foremost. ResultsThe results demonstrated from the research establish that utilising the parallelised OpenCL and Parallel Failureless Aho-Corasick (PFAC) algorithm solution demonstrates significantly greater processing improvements from the use of a single, and multiple, GPUs on modern hardware.In comparison to CPU approaches, GPGPU processing models were observed to minimised the amount of time required to search for greater amounts of patterns.Results also showed that employing PFAC also delivers significant performance increases over the BM algorithm.The method employed to read data from storage devices was also seen to have a significant effect on the time required to perform string searching and file carving. ConclusionsEmpirical testing shows that the proposed string searching method is believed to be more efficient than the widely-adopted Boyer-Moore algorithms when applied to string searching and performing file carving.The developed OpenCL GPGPU processing framework was found to be more efficient than CPU counterparts when searching for greater amounts of patterns within data.This research also refutes claims that file carving is solely limited by the performance of the storage device, and presents compelling evidence that performance is bound by the combination of the performance of the storage device and processing technique employed.vi
Cited by 0Open access
Akhtar Rasool, Nilay Khare · 2013
String matching is a classical problem in computer science. After the study of the Naïve string search, Brute Force and the KMP algorithm, several advantages and disadvantages of the algorithms have been analyzed. Considering KMP in particular concept of parallelization has been introduced to improve the performance of the KMP algorithm. The algorithm is designed to work on SIMD parallel architecture where text is divided for parallel processing and special searching at division point is required for consistent and complete searching. This algorithm reduces the number of comparisons and parallelization improves the time efficiency. This algorithm achieves a better result as compared to the multithreaded version of the algorithm where again by text dividing, the parallelization is achieved.
Cited by 0
Ethan Bayne · Abertay Research Portal (Abertay University)
BackgroundString searching within a large corpus of data is a critical component of digital forensic (DF) analysis techniques such as file carving.The continuing increase in capacity of consumer storage devices requires similar improvements to the performance of string searching techniques employed by DF tools used to analyse forensic data.As string searching is a trivially-parallelisable problem, general purpose graphic processing unit (GPGPU) approaches are a natural fit.Currently, only some of the research in employing GPGPU programming has been transferred to the field of DF, of which, a closed-source GPGPU framework was used-Complete Unified Device Architecture (CUDA).Findings from these earlier studies have found that local storage devices from which forensic data are read present an insurmountable performance bottleneck. AimThis research hypothesises that modern storage devices no longer present a performance bottleneck to the currently used processing techniques of the field, andproposes that an open-standards GPGPU framework solution -Open Computing Language (OpenCL) -would be better suited to accelerate file carving with wider compatibility across an array of modern GPGPU hardware.This research further hypothesises that a modern multi-string searching algorithm may be better adapted to fulfil the requirements of DF investigation. MethodsThis research presents a review of existing research and tools used to perform file carving and acknowledges related work within the field.To test the hypothesis, parallel v file carving software was created using C# and OpenCL, employing both a traditional string searching algorithm and a modern multi-string searching algorithm to conduct an analysis of forensic data.A set of case studies that demonstrate and evaluate potential benefits of adopting various methods in conducting string searching on forensic data are given.This research concludes with a final case study which evaluates the performance to perform file carving with the best-proposed string searching solution and compares the result with an existing file carving tool-Foremost. ResultsThe results demonstrated from the research establish that utilising the parallelised OpenCL and Parallel Failureless Aho-Corasick (PFAC) algorithm solution demonstrates significantly greater processing improvements from the use of a single, and multiple, GPUs on modern hardware.In comparison to CPU approaches, GPGPU processing models were observed to minimised the amount of time required to search for greater amounts of patterns.Results also showed that employing PFAC also delivers significant performance increases over the BM algorithm.The method employed to read data from storage devices was also seen to have a significant effect on the time required to perform string searching and file carving. ConclusionsEmpirical testing shows that the proposed string searching method is believed to be more efficient than the widely-adopted Boyer-Moore algorithms when applied to string searching and performing file carving.The developed OpenCL GPGPU processing framework was found to be more efficient than CPU counterparts when searching for greater amounts of patterns within data.This research also refutes claims that file carving is solely limited by the performance of the storage device, and presents compelling evidence that performance is bound by the combination of the performance of the storage device and processing technique employed.vi
Cited by 0Open access
Ahmad F. Klaib, Hugh Osborne · University of Huddersfield Repository (University of Huddersfield) · 2008
Huge amounts of data are stored in linear files. This is also the case for biological data. Biological proteins are sequences of amino acids. The quantities of data in these fields tend to increase year on year. For this reason efficient string-matching algorithms should be used which use minimal computer storage and which minimize the searching response time. In this paper, we propose a new algorithm called BRBMH algorithm which offers improved number of comparison and elapsed searching time when compared to the well-known algorithms such as BF, KMP, BM, BMH, KR, ZT, QS, BR, FS, SSABS, TVSBS, ZTBMH and BRFS algorithms. The experimental results show that the new algorithm is faster and perform fewer numbers of comparisons than other compared algorithms for any length of alphabets and patterns. So the proposed algorithm is applicable for searching protein sequence databases as well as in any other string searching applications.
Cited by 2
Putra, Henryco Rahardian Gotama · Unika Repositor (Unika) · 2011
Spare Part Book Application is a program to storing and searching data \nabout item of spare part motor cycle. This program can searching data item in \ntext file. This program also can find the similar string in text file. If data string is \nfind, this program will show how many data is fine and block the similar string in \ntext area. This program will show information if data can't find. \nThis program created with Java Language Programming and use \nGUI (Graphical User Interface) programming to the performance. This project \nuses Single Linked List as a data structure and Colussi as an algorithm to fine the \ndata. Algorithm colussi is an algorithm that comparing the similar words.
Cited by 0Open access
Juby Mathew, Anchana Ashok, Sumy Roslin Joseph et al. · Zenodo (CERN European Organization for Nuclear Research) · 2019
The string-searching algorithms, also called string-matching algorithms, are a significant class of string algorithms. The objective of these algorithms is to discover a place where one or a few strings (likewise called patterns) are found inside a larger string or text. Nowadays there are numerous algorithms accessible for string looking with changed seeking speed. The larger the move of the pattern with respect to the string if there should be an occurrence of pattern and string characters' confound is, the higher is the algorithm running speed. This paper offers an algorithm, which has been created based on the Kunth-Morris-Pratt string looking algorithm. This algorithm depends on different fundamental standards of pattern matching. Knuth-Morris-Pratt algorithm depends on forwarding pattern and the pattern is completely contrasted and the selected text window (STW) of the text string and show the beginning index position.
Cited by 0Open access
Panagiotis D. Michailidis, Konstantinos G. Margaritis · 2003
Abstract:- This paper presents a processor array design for flexible approximate string matching. Initially, a sequential algorithm is discussed which consists of two phases, i.e. preprocessing and searching. Then, starting from the computational schedule of the searching phase a parallel architecture is derived. Further, the preprocessing phase is also accomodated onto the same architecture. Key-Words:- Approximate string matching; processor arrays; parallel architecture 1
Cited by 0
Klaib, Ahmad, Osborne, Hugh · University of Huddersfield Repository (University of Huddersfield) · 2009
String matching algorithms play a key role in many \ncomputer science problems, and in the implementation of \ncomputer software. This problem has received, and \ncontinues to receive a great deal of attention due to \nvarious applications in text manipulation, information \nretrieval, speech recognition, image and signal \nprocessing and computational biology. In this study, we \npropose a new algorithm called the Odd and Even \nalgorithm (OE). OE combines an enhanced preprocessing \nphase from the Berry Ravindran algorithm with our \nproposed new searching phase procedure. This variety of \nsearching order allows our proposed algorithm to reduce \nthe number of comparison characters and enhances the \nsearching response time. Experimental results show that \nOE algorithm offers a smaller number of comparisons \nand offers improved elapsed searching time when \ncompared to other well-known algorithms for searching \nany length of alphabets and patterns. The proposed \nalgorithm is applicable to searching protein sequence \ndatabases as well as any other string searching \napplications.
Cited by 1Open access