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Offline compression by greedy textual substitution
 PROC. IEEE
, 2000
"... Greedy offline textual substitution refers to the following approach to compression or structural inference. Given a long textstring x, a substring w is identified such that replacing all instances of w in x except one by a suitable pair of pointers yields the highest possible contraction of x; the ..."
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Cited by 25 (1 self)
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Greedy offline textual substitution refers to the following approach to compression or structural inference. Given a long textstring x, a substring w is identified such that replacing all instances of w in x except one by a suitable pair of pointers yields the highest possible contraction of x; the process is then repeated on the contracted textstring until substrings capable of producing contractions can no longer be found. This paper examines computational issues arising in the implementation of this paradigm and describes some applications and experiments.
Algorithms on Compressed Strings and Arrays
 In Proc. 26th Ann. Conf. on Current Trends in Theory and Practice of Infomatics
, 1999
"... . We survey the complexity issues related to several algorithmic problems for compressed one and twodimensional texts without explicit decompression: patternmatching, equalitytesting, computation of regularities, subsegment extraction, language membership, and solvability of word equations. Our ..."
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Cited by 18 (0 self)
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. We survey the complexity issues related to several algorithmic problems for compressed one and twodimensional texts without explicit decompression: patternmatching, equalitytesting, computation of regularities, subsegment extraction, language membership, and solvability of word equations. Our basic problem is one and twodimensional patternmatching together with its variations. For some types of compression the patternmatching problems are infeasible (NPhard), for other types they are solvable in polynomial time and we discuss how to reduce the degree of corresponding polynomials. 1 Introduction In the last decade a new stream of research related to data compression has emerged: algorithms on compressed objects. It has been caused by the increase in the volume of data and the need to store and transmit masses of information in compressed form. The compressed information has to be quickly accessed and processed without explicit decompression. In this paper we consider severa...
Some Theory and Practice of Greedy Offline Textual Substitution
 Proc. Data Compression Conference, IEEE Computer
, 1998
"... Purdue University and Universit�a di Padova Greedy o��line textual substitution refers to the following steepest descent approach ..."
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Cited by 16 (0 self)
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Purdue University and Universit�a di Padova Greedy o��line textual substitution refers to the following steepest descent approach
An Optimal O(log log n) Time Parallel Algorithm for Detecting all Squares in a String
, 1995
"... An optimal O(log log n) time concurrentread concurrentwrite parallel algorithm for detecting all squares in a string is presented. A tight lower bound shows that over general alphabets this is the fastest possible optimal algorithm. When p processors are available the bounds become \Theta(d n ..."
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Cited by 11 (6 self)
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An optimal O(log log n) time concurrentread concurrentwrite parallel algorithm for detecting all squares in a string is presented. A tight lower bound shows that over general alphabets this is the fastest possible optimal algorithm. When p processors are available the bounds become \Theta(d n log n p e + log log d1+p=ne 2p). The algorithm uses an optimal parallel stringmatching algorithm together with periodicity properties to locate the squares within the input string.
Efficient String Algorithmics
, 1992
"... Problems involving strings arise in many areas of computer science and have numerous practical applications. We consider several problems from a theoretical perspective and provide efficient algorithms and lower bounds for these problems in sequential and parallel models of computation. In the sequ ..."
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Cited by 8 (6 self)
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Problems involving strings arise in many areas of computer science and have numerous practical applications. We consider several problems from a theoretical perspective and provide efficient algorithms and lower bounds for these problems in sequential and parallel models of computation. In the sequential setting, we present new algorithms for the string matching problem improving the previous bounds on the number of comparisons performed by such algorithms. In parallel computation, we present tight algorithms and lower bounds for the string matching problem, for finding the periods of a string, for detecting squares and for finding initial palindromes.
Optimal Parallel Dictionary Matching and Compression (Extended Abstract)
 7th Annual ACM Symposium on Parallel Algorithms and Architectures
, 1995
"... ) Martin Farach S. Muthukrishnan y Rutgers University DIMACS April 26, 1995 Abstract Emerging applications in multimedia and the Human Genome Project require storage and searching of large databases of strings  a task for which parallelism seems the only hope. In this paper, we consider the ..."
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Cited by 7 (3 self)
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) Martin Farach S. Muthukrishnan y Rutgers University DIMACS April 26, 1995 Abstract Emerging applications in multimedia and the Human Genome Project require storage and searching of large databases of strings  a task for which parallelism seems the only hope. In this paper, we consider the parallelism in some of the fundamental problems in compressing strings and in matching large dictionaries of patterns against texts. We present the first workoptimal algorithms for these wellstudied problems including the classical dictionary matching problem, optimal compression with a static dictionary and the universal data compression with dynamic dictionary of Lempel and Ziv. All our algorithms are randomized and they are of the Las Vegas type. Furthermore, they are fast, working in time logarithmic in the input size. Additionally, our algorithms seem suitable for a distributed implementation. 1 Introduction Large data bases of strings from multimedia applications and the Human G...
String Pattern Matching For A Deluge Survival Kit
, 2000
"... String Pattern Matching concerns itself with algorithmic and combinatorial issues related to matching and searching on linearly arranged sequences of symbols, arguably the simplest possible discrete structures. As unprecedented volumes of sequence data are amassed, disseminated and shared at an incr ..."
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Cited by 5 (1 self)
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String Pattern Matching concerns itself with algorithmic and combinatorial issues related to matching and searching on linearly arranged sequences of symbols, arguably the simplest possible discrete structures. As unprecedented volumes of sequence data are amassed, disseminated and shared at an increasing pace, effective access to, and manipulation of such data depend crucially on the efficiency with which strings are structured, compressed, transmitted, stored, searched and retrieved. This paper samples from this perspective, and with the authors' own bias, a rich arsenal of ideas and techniques developed in more than three decades of history.
Efficient String Matching on Coded Texts
 In Proceedings of Combinatorial Pattern Matching, 6th Annual Symposium (CPM'95
, 1994
"... The so called "four Russians technique" is often used to speed up algorithms by encoding several data items in a single memory cell. Given a sequence of n symbols over a constant size alphabet, one can encode the sequence into O(n=) memory cells in O(log ) time using n= log processors. This paper ..."
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Cited by 2 (1 self)
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The so called "four Russians technique" is often used to speed up algorithms by encoding several data items in a single memory cell. Given a sequence of n symbols over a constant size alphabet, one can encode the sequence into O(n=) memory cells in O(log ) time using n= log processors. This paper presents an efficient CRCWPRAM stringmatching algorithm for coded texts that takes O(log log(m=)) time 1 making only O(n=) operations, an improvement by a factor of = O(logn) on the number of operations used in previous algorithms. Using this stringmatching algorithm one can test if a string is squarefree and find all palindromes in a string in O(log log n) time using n= log log n processors. 1 Introduction In the stringmatching problem one is searching for occurrences of a pattern string P[1::m] in a text string T [1::n]. There exist several O(n + m) time sequential stringmatching algorithms that are used in a large variety of applications. Galil [23] published the first efficient...
On the Complexity of Computing the Order of Repetition of a String
, 1998
"... We show a simple O(n log n) time algorithm computing the order of repetition in a string. A parallel version of the algorithm works in O(log ..."
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We show a simple O(n log n) time algorithm computing the order of repetition in a string. A parallel version of the algorithm works in O(log
Detecting all Squares in a String ∗
"... is permitted for educational or research use on condition that this copyright notice is included in any copy. See back inner page for a list of recent publications in the BRICS Report Series. Copies may be obtained by contacting: BRICS ..."
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is permitted for educational or research use on condition that this copyright notice is included in any copy. See back inner page for a list of recent publications in the BRICS Report Series. Copies may be obtained by contacting: BRICS