Trans-dichotomous algorithms for minimum spanning trees and shortest paths
Journal of Computer and System Sciences - Special issue: 31st IEEE conference on foundations of computer science, Oct. 22–24, 1990
String matching in Lempel-Ziv compressed strings
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
Let sleeping files lie: pattern matching in Z-compressed files
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
A fast string searching algorithm
Communications of the ACM
String Matching Algorithms and Automata
Proceedings of the Colloquium in Honor of Arto Salomaa on Results and Trends in Theoretical Computer Science
LATIN '00 Proceedings of the 4th Latin American Symposium on Theoretical Informatics
Pattern Matching in Compressed Texts
Proceedings of the 15th Conference on Foundations of Software Technology and Theoretical Computer Science
A General Practical Approach to Pattern Matching over Ziv-Lempel Compressed Text
CPM '99 Proceedings of the 10th Annual Symposium on Combinatorial Pattern Matching
Almost Optimal Fully LZW-Compressed Pattern Matching
DCC '99 Proceedings of the Conference on Data Compression
Optimal suffix tree construction with large alphabets
FOCS '97 Proceedings of the 38th Annual Symposium on Foundations of Computer Science
Algorithms on Strings
A universal algorithm for sequential data compression
IEEE Transactions on Information Theory
Simple and efficient LZW-compressed multiple pattern matching
Journal of Discrete Algorithms
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We consider the following variant of the classical pattern matching problem: given an uncompressed pattern p[1..m] and a compressed representation of a string t[1..N], does p occur in t? When t is compressed using the LZW method, we are able to detect the occurrence in optimal linear time, thus answering a question of Amir et al. [1994]. Previous results implied solutions with complexities O(n log m + m) Amir et al. [1994], O(n + m1+ε) [Kosaraju 1995], or (randomized) O(n log Nn + m) [Farach and Thorup 1995], where n is the size of the compressed representation of t. Our algorithm is conceptually simple and fully deterministic.