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74
A Guided Tour to Approximate String Matching
 ACM COMPUTING SURVEYS
, 1999
"... We survey the current techniques to cope with the problem of string matching allowing errors. This is becoming a more and more relevant issue for many fast growing areas such as information retrieval and computational biology. We focus on online searching and mostly on edit distance, explaining t ..."
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Cited by 598 (36 self)
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We survey the current techniques to cope with the problem of string matching allowing errors. This is becoming a more and more relevant issue for many fast growing areas such as information retrieval and computational biology. We focus on online searching and mostly on edit distance, explaining the problem and its relevance, its statistical behavior, its history and current developments, and the central ideas of the algorithms and their complexities. We present a number of experiments to compare the performance of the different algorithms and show which are the best choices according to each case. We conclude with some future work directions and open problems.
NRgrep: A Fast and Flexible Pattern Matching Tool
 Software Practice and Experience (SPE
, 2000
"... We present nrgrep ("nondeterministic reverse grep"), a new pattern matching tool designed for efficient search of complex patterns. Unlike previous tools of the grep family, such as agrep and Gnu grep, nrgrep is based on a single and uniform concept: the bitparallel simulation of a non ..."
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Cited by 46 (7 self)
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We present nrgrep ("nondeterministic reverse grep"), a new pattern matching tool designed for efficient search of complex patterns. Unlike previous tools of the grep family, such as agrep and Gnu grep, nrgrep is based on a single and uniform concept: the bitparallel simulation of a nondeterministic suffix automaton. As a result, nrgrep can find from simple patterns to regular expressions, exactly or allowing errors in the matches, with an efficiency that degrades smoothly as the complexity of the searched pattern increases. Another concept fully integrated into nrgrep and that contributes to this smoothness is the selection of adequate subpatterns for fast scanning, which is also absent in many current tools. We show that the efficiency of nrgrep is similar to that of the fastest existing string matching tools for the simplest patterns, and by far unpaired for more complex patterns.
Substring selectivity estimation
 In Proceedings of the ACM Symposium on Principles of Database Systems
, 1999
"... We study the problem of estimating selectivity of approximate substring queries. Its importance in databases is ever increasing as more and more data are input by users and are integrated with many typographical errors and different spelling conventions. To begin with, we consider edit distance for ..."
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Cited by 33 (5 self)
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We study the problem of estimating selectivity of approximate substring queries. Its importance in databases is ever increasing as more and more data are input by users and are integrated with many typographical errors and different spelling conventions. To begin with, we consider edit distance for the similarity between a pair of strings. Based on information stored in an extended Ngram table, we propose two estimation algorithms, MOF and LBS for the task. The latter extends the former with ideas from set hashing signatures. The experimental results show that MOF is a lightweight algorithm that gives fairly accurate estimations. However, if more space is available, LBS can give better accuracy than MOF and other baseline methods. Next, we extend the proposed solution to other similarity predicates, SQL LIKE operator and Jaccard similarity. 1.
Extending Qgrams to estimate selectivity of string matching with low edit distance
 In VLDB
, 2007
"... There are many emerging database applications that require accurate selectivity estimation of approximate string matching queries. Edit distance is one of the most commonly used string similarity measures. In this paper, we study the problem of estimating selectivity of string matching with low edit ..."
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Cited by 27 (2 self)
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There are many emerging database applications that require accurate selectivity estimation of approximate string matching queries. Edit distance is one of the most commonly used string similarity measures. In this paper, we study the problem of estimating selectivity of string matching with low edit distance. Our framework is based on extending qgrams with wildcards. Based on the concepts of replacement semilattice, string hierarchy and a combinatorial analysis, we develop the formulas for selectivity estimation and provide the algorithm BasicEQ. We next develop the algorithm OptEQ by enhancing BasicEQ with two novel improvements. Finally we show a comprehensive set of experiments using three benchmarks comparing OptEQ with the stateoftheart method SEP IA. Our experimental results show that OptEQ delivers more accurate selectivity estimations. 1.
Bitparallel Witnesses and their Applications to Approximate String Matching
 Algorithmica
, 2005
"... We present a new bitparallel technique for approximate string matching. We build on two previous techniques. The first one, BPM [Myers, J. of the ACM, 1999], searches for a pattern of length m in a text of length n permitting k differences in O(⌈m/w⌉n) time, where w is the width ..."
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Cited by 21 (2 self)
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We present a new bitparallel technique for approximate string matching. We build on two previous techniques. The first one, BPM [Myers, J. of the ACM, 1999], searches for a pattern of length m in a text of length n permitting k differences in O(&lceil;m/w&rceil;n) time, where w is the width of the computer word. The second one, ABNDM [Navarro and Raffinot, ACM JEA, 2000], extends a sublineartime exact algorithm to approximate searching. ABNDM relies on another algorithm, BPA [Wu and Manber, Comm. ACM, 1992], which makes use of an O(k&lceil;m/w&rceil;n) time algorithm for its internal workings. BPA is slow but flexible enough to support all operations required by ABNDM. We improve previous ABNDM analyses, showing that it is averageoptimal in number of inspected characters, although the overall complexity is higher because of the O(k&lceil;m/w&rceil;) work done per inspected character. We then show that the faster BPM can be adapted to support all the operations required by ABNDM. This involves extending it to compute edit distance, to search for any pattern suffix, and to detect in advance the impossibility of a later match. The solution to those challenges is based on the concept of a witness, which permits sampling some dynamic programming matrix values so as to bound, deduce, or compute others fast. The resulting algorithm is averageoptimal for m &le; w, assuming the alphabet size is constant. In practice, it performs better than the original ABNDM and is the fastest algorithm for several combinations of m, k and alphabet sizes that are useful, for example, in natural language searching and computational biology. To show that the concept of witnesses can be used in further scenarios, we also improve a recent bitparallel algorithm based on Myers [Fredriksson, SPIRE 2003]. The use of witn...
Multipattern string matching with qgrams
 ACM Journal of Experimental Algorithmics
, 2006
"... We present three algorithms for exact string matching of multiple patterns. Our algorithms are filtering methods, which apply qgrams and bit parallelism. We ran extensive experiments with them and compared them with various versions of earlier algorithms, e.g. different trie implementations of the ..."
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Cited by 20 (6 self)
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We present three algorithms for exact string matching of multiple patterns. Our algorithms are filtering methods, which apply qgrams and bit parallelism. We ran extensive experiments with them and compared them with various versions of earlier algorithms, e.g. different trie implementations of the AhoCorasick algorithm. All of our algorithms showed to be substantially faster than earlier solutions for sets of 1,000–10,000 patterns and the good performance of two of them continues to 100,000 patterns. The gain is due to the improved filtering efficiency caused by qgrams.
Alternative algorithms for bitparallel string matching
 In Proc SPIRE’03, Lecture Notes in Computer Science 2857:80–93
, 2003
"... Abstract. We consider bitparallel algorithms of BoyerMoore type for exact string matching. We introduce a twoway modification of the BNDM algorithm. If the text character aligned with the end of the pattern is a mismatch, we continue by examining text characters after the alignment. Besides this ..."
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Cited by 19 (6 self)
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Abstract. We consider bitparallel algorithms of BoyerMoore type for exact string matching. We introduce a twoway modification of the BNDM algorithm. If the text character aligned with the end of the pattern is a mismatch, we continue by examining text characters after the alignment. Besides this twoway variation, we present a simplified version of BNDM without prefix search and an algorithm scheme for long patterns. We also study a different bitparallel algorithm, which keeps the history of examined characters in a bitvector and where shifting is based on this bitvector. We report experiments where we compared the new algorithms with existing ones. The simplified BNDM is the most promising of the new algorithms in practice. 1
The exact online string matching problem: a review of the most recent results
 ACM COMPUTING SURVEYS
, 2013
"... This article addresses the online exact string matching problem which consists in finding all occurrences of a given pattern p in a text t. It is an extensively studied problem in computer science, mainly due to its direct applications to such diverse areas as text, image and signal processing, spee ..."
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Cited by 14 (6 self)
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This article addresses the online exact string matching problem which consists in finding all occurrences of a given pattern p in a text t. It is an extensively studied problem in computer science, mainly due to its direct applications to such diverse areas as text, image and signal processing, speech analysis and recognition, information retrieval, data compression, computational biology and chemistry. In the last decade more than 50 new algorithms have been proposed for the problem, which add up to a wide set of (almost 40) algorithms presented before 2000. In this article we review the string matching algorithms presented in the last decade and present experimental results in order to bring order among the dozens of articles published in this area.
Pattern Matching in Compressed Text and Images
, 2001
"... Normally compressed data needs to be decompressed before it is processed, but if the compression has been done in the fight way, it is often possible to search the data without having to decompress it, or at least only partially decompress it. The problem can be divided into lossless and lossy c ..."
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Cited by 13 (11 self)
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Normally compressed data needs to be decompressed before it is processed, but if the compression has been done in the fight way, it is often possible to search the data without having to decompress it, or at least only partially decompress it. The problem can be divided into lossless and lossy compression methods, and then in each of these cases the pattern matching can be either exact or inexact. Much work has been reported in the literature on techniques for all of these cases, including algorithms that are suitable for pattern matching for various compression methods, and compression methods designed specifically for pattern matching. This work is surveyed in this paper. The paper also exposes the important relationship between pattern matching and compression, and proposes some performance measures for compressed pattern matching algorithms. Ideas and directions for future work are also described.
Compact DFA Representation for Fast Regular Expression Search
, 2001
"... . We present a new technique to encode a deterministic finite automaton (DFA). Based on the specific properties of Glushkov's nondeterministic finite automaton (NFA) construction algorithm, we are able to encode the DFA using (m + 1)(2 m+1 + j\Sigma j) bits, where m is the number of charact ..."
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Cited by 13 (6 self)
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. We present a new technique to encode a deterministic finite automaton (DFA). Based on the specific properties of Glushkov's nondeterministic finite automaton (NFA) construction algorithm, we are able to encode the DFA using (m + 1)(2 m+1 + j\Sigma j) bits, where m is the number of characters (excluding operator symbols) in the regular expression and \Sigma is the alphabet. This compares favorably against the worst case of (m+1)2 m+1 j\Sigma j bits needed by a classical DFA representation and m(2 2m+1 + j\Sigma j) bits needed by the Wu and Manber approach implemented in Agrep. Our approach is practical and simple to implement, and it permits searching regular expressions of moderate size (which include most cases of interest) faster than with any previously existing algorithm, as we show experimentally. 1