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94
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.
FiniteState Transducers in Language and Speech Processing
 Computational Linguistics
, 1997
"... Finitestate machines have been used in various domains of natural language processing. We consider here the use of a type of transducers that supports very efficient programs: sequential transducers. We recall classical theorems and give new ones characterizing sequential stringtostring transducer ..."
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Cited by 392 (42 self)
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Finitestate machines have been used in various domains of natural language processing. We consider here the use of a type of transducers that supports very efficient programs: sequential transducers. We recall classical theorems and give new ones characterizing sequential stringtostring transducers. Transducers that output weights also play an important role in language and speech processing. We give a specific study of stringtoweight transducers, including algorithms for determinizing and minimizing these transducers very efficiently, and characterizations of the transducers admitting determinization and the corresponding algorithms. Some applications of these algorithms in speech recognition are described and illustrated. 1.
Compressed suffix arrays and suffix trees with applications to text indexing and string matching
, 2005
"... The proliferation of online text, such as found on the World Wide Web and in online databases, motivates the need for spaceefficient text indexing methods that support fast string searching. We model this scenario as follows: Consider a text T consisting of n symbols drawn from a fixed alphabet Σ. ..."
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Cited by 239 (20 self)
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The proliferation of online text, such as found on the World Wide Web and in online databases, motivates the need for spaceefficient text indexing methods that support fast string searching. We model this scenario as follows: Consider a text T consisting of n symbols drawn from a fixed alphabet Σ. The text T can be represented in n lg Σ  bits by encoding each symbol with lg Σ  bits. The goal is to support fast online queries for searching any string pattern P of m symbols, with T being fully scanned only once, namely, when the index is created at preprocessing time. The text indexing schemes published in the literature are greedy in terms of space usage: they require Ω(n lg n) additional bits of space in the worst case. For example, in the standard unit cost RAM, suffix trees and suffix arrays need Ω(n) memory words, each of Ω(lg n) bits. These indexes are larger than the text itself by a multiplicative factor of Ω(lg Σ  n), which is significant when Σ is of constant size, such as in ascii or unicode. On the other hand, these indexes support fast searching, either in O(m lg Σ) timeorinO(m +lgn) time, plus an outputsensitive cost O(occ) for listing the occ pattern occurrences. We present a new text index that is based upon compressed representations of suffix arrays and suffix trees. It achieves a fast O(m / lg Σ  n +lgɛ Σ  n) search time in the worst case, for any constant
Reducing the Space Requirement of Suffix Trees
 Software – Practice and Experience
, 1999
"... We show that suffix trees store various kinds of redundant information. We exploit these redundancies to obtain more space efficient representations. The most space efficient of our representations requires 20 bytes per input character in the worst case, and 10.1 bytes per input character on average ..."
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Cited by 145 (12 self)
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We show that suffix trees store various kinds of redundant information. We exploit these redundancies to obtain more space efficient representations. The most space efficient of our representations requires 20 bytes per input character in the worst case, and 10.1 bytes per input character on average for a collection of 42 files of different type. This is an advantage of more than 8 bytes per input character over previous work. Our representations can be constructed without extra space, and as fast as previous representations. The asymptotic running times of suffix tree applications are retained. Copyright © 1999 John Wiley & Sons, Ltd. KEY WORDS: data structures; suffix trees; implementation techniques; space reduction
A subquadratic sequence alignment algorithm for unrestricted scoring matrices
 SIAM J. Comput
"... Abstract The classical algorithm for computing the similarity between two sequences Our algorithm applies to both local and global alignment computations. The speedup is achieved by dividing the dynamic programming matrix into variable sized blocks, as induced by LempelZiv parsing of both string ..."
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Cited by 76 (5 self)
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Abstract The classical algorithm for computing the similarity between two sequences Our algorithm applies to both local and global alignment computations. The speedup is achieved by dividing the dynamic programming matrix into variable sized blocks, as induced by LempelZiv parsing of both strings, and utilizing the inherent periodic nature of both strings. This leads to an O(n2/logn) algorithm for an input of constant alphabet size. For most texts, the time complexity is actually O(hn2/logn) where h _< 1 is the entropy of the text.
Fast and Flexible String Matching by Combining Bitparallelism and Suffix Automata
 ACM JOURNAL OF EXPERIMENTAL ALGORITHMICS (JEA
, 1998
"... ... In this paper we merge bitparallelism and suffix automata, so that a nondeterministic suffix automaton is simulated using bitparallelism. The resulting algorithm, called BNDM, obtains the best from both worlds. It is much simpler to implement than BDM and nearly as simple as ShiftOr. It inher ..."
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Cited by 74 (10 self)
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... In this paper we merge bitparallelism and suffix automata, so that a nondeterministic suffix automaton is simulated using bitparallelism. The resulting algorithm, called BNDM, obtains the best from both worlds. It is much simpler to implement than BDM and nearly as simple as ShiftOr. It inherits from ShiftOr the ability to handle flexible patterns and from BDM the ability to skip characters. BNDM is 30%40% faster than BDM and up to 7 times faster than ShiftOr. When compared to the fastest existing algorithms on exact patterns (which belong to the BM family), BNDM is from 20% slower to 3 times faster, depending on the alphabet size. With respect to flexible pattern searching, BNDM is by far the fastest technique to deal with classes of characters and is competitive to search allowing errors. In particular, BNDM seems very adequate for computational biology applications, since it is the fastest algorithm to search on DNA sequences and flexible searching is an important problem in that
Approximate string matching over suffix trees
 PROCEEDINGS OF THE 4TH ANNUAL SYMPOSIUM ON COMBINATORIAL PATTERN MATCHING, NUMBER 684 IN LECTURE NOTES IN COMPUTER SCIENCE
, 1993
"... The classical approximate stringmatching problem of finding the locations of approximate occurrences P 0 of pattern string P in text string T such that the edit distance between P and P 0 is k is considered. We concentrate on the special case in which T is available for preprocessing before the se ..."
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Cited by 70 (1 self)
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The classical approximate stringmatching problem of finding the locations of approximate occurrences P 0 of pattern string P in text string T such that the edit distance between P and P 0 is k is considered. We concentrate on the special case in which T is available for preprocessing before the searches with varying P and k. It is shown how the searches can be done fast using the suffix tree of T augmented with the suffix links as the preprocessed form of T and applying dynamic programming over the tree. Three variations of the search algorithm are developed with running times O(mq + n), O(mq log q + size of the output), and O(m
On Some Applications of FiniteState Automata Theory to Natural Language Processing
 Journal of Natural Language Engineering
, 1996
"... We describe new applications of the theory of automata to natural language processing: the representation of very large scale dictionaries and the indexation of natural language texts. They are based on new algorithms that we introduce and describe in detail. In particular, we give pseudocodes for t ..."
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Cited by 64 (11 self)
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We describe new applications of the theory of automata to natural language processing: the representation of very large scale dictionaries and the indexation of natural language texts. They are based on new algorithms that we introduce and describe in detail. In particular, we give pseudocodes for the determinization of string to string transducers, the deterministic union of psubsequential string to string transducers, and the indexation by automata. We report several experiments illustrating the applications. 1 Introduction The theory of automata provides efficient and convenient tools for the representation of linguistic phenomena. Natural language processing can even be considered as one of the major fields of application of this theory (Perrin 1993). The use of finitestate machines has already been shown to be successful in various areas of computational linguistics: lexical analysis (Silberztein 1993), morphology and phonology (Koskenniemi 1985; Karttunen et al. 1992; Kaplan a...