A Two-Hashing Table Multiple String Pattern Matching Algorithm (original) (raw)
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To analyze the content of the documents, the various pattern matching algorithms are used to find all the occurrences of a limited set of patterns within an input text or input document. In order to perform this task, this research work used four existing string matching algorithms; they are Brute Force algorithm, Knuth-Morris-Pratt algorithm (KMP), Boyer Moore algorithm and Rabin Karp algorithm. This work also proposes three new string matching algorithms. They are Enhanced Boyer Moore algorithm, Enhanced Rabin Karp algorithm and Enhanced Knuth-Morris-Pratt algorithm. Findings: For experimentation, this work has used two types of documents, i.e. .txt and .docx. Performance measures used are search time, number of iterations and accuracy. From the experimental results, it is realized that the enhanced KMP algorithm gives better accuracy compared to other string matching algorithms. Application/Improvements: Normally, these algorithms are used in the field of text mining, document cl...
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String matching is one of the most important concept used in computer science in various real life applications like as Intrusion detection system, Data mining, Plagiarism detection system. There are many string matching algorithms which help to find pattern from the text. These algorithms are categorized in single string matching and multiple string matching. The Wu-Manber (WM) algorithm is multiple patterns algorithm which is the finest string matching algorithm. The performance of WM depends on various table build in pre processing phase these are prefix table, shift table and hase table. We introduce a new algorithm namely the Efficient Wu Manber algorithm (EWM) algorithm which is advance version of Wu Manber algorithm with respect to time. Efficient Wu-Manber Algorithm eliminate the prefix table which is unused most of the cases in wu manber, construct two shift table instead of single shift table and uses nonlinear data structure i.e. AVL tree instead of linear data structure i.e. linked list used in WM in Hash table, which reduce the traversed number of nodes to find exact match. The experimental results and analysis show that EWM algorithm has better performance as compare to WM and its existing improved algorithm and also better from various string matching
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Present paper describes the details of the study of the work that has been done in the field of text searching, a subdivision of Natural Language Processing (NLP) till date. The work in this project includes the study and analysis of some of the algorithms devised under this topic, finding the faults or loopholes and trying to increase the efficiency of these algorithms devised, taking forward the range of work done on it. Experiment is done on the various text search algorithms that have been devised namely Knuth-Morris Pratt Algorithm, Naïve Search Algorithm and Boyer-Moore Algorithm by providing text input of various sizes and analyzing their behavior on these variable inputs. After analyzing and doing the study on these algorithms the results states that Boyer-Moore"s Algorithm worked quite well and efficiently than the rest of them when dealing with larger data sets. When working on larger alphabets the Knuth-Morris Pratt Algorithm works quite well. These algorithms do have drawbacks as their efficiency depends upon the alphabet/pattern size. And also this paper describes new pattern matching algorithm that uses delimiter for shifting the pattern while matching.
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Exact String matching algorithms has been very significant in many applications in the last two decades. This is due to the advancement in technology that produces large volumes of data. The main factors in string matching algorithms are the number of attempts, the number of character comparison and the running time. These factors are influenced by the type of algorithm, type of data, data size and length of pattern used. In this article, we perform review for advantages and disadvantages of executing exact string matching algorithm. We conclude that the suffix automata and hybrid are the faster algorithms with the lowest number of attempts and the hashing approaches have the lower number of comparison. The bit parallelism algorithms have the similar limitations.
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Software: Practice and Experience, 2001
We present a string matching or pattern matching method which is especially useful when a single block of text must be searched repeatedly for different patterns. The method combines linking the text according to digrams, searching on the least-frequent digram, and probing selected characters as a preliminary filter before full pattern comparison. Tests on real alphabetic data show that the number of character comparisons may be decreased by two orders of magnitude compared with Knuth-Morris-Pratt and similar searching, but with an initialization overhead comparable to five to ten conventional searches.