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14
OnLine Construction of Suffix Trees
, 1995
"... An online algorithm is presented for constructing the suffix tree for a given string in time linear in the length of the string. The new algorithm has the desirable property of processing the string symbol by symbol from left to right. It has always the suffix tree for the scanned part of the strin ..."
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Cited by 437 (2 self)
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An online algorithm is presented for constructing the suffix tree for a given string in time linear in the length of the string. The new algorithm has the desirable property of processing the string symbol by symbol from left to right. It has always the suffix tree for the scanned part of the string ready. The method is developed as a lineartime version of a very simple algorithm for (quadratic size) suffix tries. Regardless of its quadratic worstcase this latter algorithm can be a good practical method when the string is not too long. Another variation of this method is shown to give in a natural way the wellknown algorithms for constructing suffix automata (DAWGs).
From Ukkonen to McCreight and Weiner: A Unifying View of LinearTime Suffix Tree Constructions
 ALGORITHMICA
, 1997
"... We review the linear time suffix tree constructions by Weiner, McCreight, and Ukkonen. We use the terminology of the most recent algorithm, Ukkonen's online construction, to explain its historic predecessors. This reveals relationships much closer than one would expect, since the three algorith ..."
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Cited by 86 (7 self)
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We review the linear time suffix tree constructions by Weiner, McCreight, and Ukkonen. We use the terminology of the most recent algorithm, Ukkonen's online construction, to explain its historic predecessors. This reveals relationships much closer than one would expect, since the three algorithms are based on rather different intuitive ideas. Moreover, it completely explains the dierences between these algorithms in terms of simplicity, efficiency, and implementation complexity.
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
Matching a Set of Strings with Variable Length Don’t Cares, Theoretical Computer Science 178
, 1997
"... Given an alphabet A, a pattern p is a sequence (vl,...,vm) of words from A * called keywords. We represent p as a single word ..."
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Cited by 24 (4 self)
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Given an alphabet A, a pattern p is a sequence (vl,...,vm) of words from A * called keywords. We represent p as a single word
A Comparison of Imperative and Purely Functional Suffix Tree Constructions
 Science of Computer Programming
, 1995
"... We explore the design space of implementing suffix tree algorithms in the functional paradigm. We review the linear time and space algorithms of McCreight and Ukkonen. Based on a new terminology of nested suffixes and nested prefixes, we give a simpler and more declarative explanation of these algor ..."
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Cited by 22 (6 self)
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We explore the design space of implementing suffix tree algorithms in the functional paradigm. We review the linear time and space algorithms of McCreight and Ukkonen. Based on a new terminology of nested suffixes and nested prefixes, we give a simpler and more declarative explanation of these algorithms than was previously known. We design two "naive" versions of these algorithms which are not linear time, but use simpler data structures, and can be implemented in a purely functional style. Furthermore, we present a new, "lazy" suffix tree construction which is even simpler. We evaluate both imperative and functional implementations of these algorithms. Our results show that the naive algorithms perform very favourably, and in particular, the lazy construction compares very well to all the others. 1 Introduction Suffix trees are the method of choice when a large sequence of symbols, the "text", is to be searched frequently for occurrences of short sequences, the "patterns". Given tha...
WindowAccumulated Subsequence matching Problem is linear
 In Proceedings of the Eighteenth ACM SIGMODSIGACT SIGART Symposium on Principles of Database Systems: PODS 1999, ACM
, 1999
"... Given two strings, text t of length n, and pattern p = p1 : : : pk of length k, and given a natural number w, the subsequence matching problem consists in finding the number of size w windows of text t which contain pattern p as a subsequence, i.e. the letters p1 ; : : : ; pk occur in the window, i ..."
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Cited by 8 (0 self)
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Given two strings, text t of length n, and pattern p = p1 : : : pk of length k, and given a natural number w, the subsequence matching problem consists in finding the number of size w windows of text t which contain pattern p as a subsequence, i.e. the letters p1 ; : : : ; pk occur in the window, in the same order as in p, but not necessarily consecutively (they may be interleaved with other letters). Subsequence matching is used for finding frequent patterns and association rules in databases. We generalize the KnuthMorrisPratt (KMP) pattern matching algorithm; we define a nonconventional kind of RAM, the MPRAMs which model more closely the microprocessor operations; we design an O(n) online algorithm for solving the subsequence matching problem on MPRAMs. Keywords: Subsequence matching, algorithms, frequent patterns, episode matching, datamining. 1 Introduction We address the following problem. Given a text t of length n and a pattern p = p 1 \Delta \Delta \Delta p k of l...