An improved algorithm for approximate string matching
SIAM Journal on Computing
Optimal prefetching via data compression (extended abstract)
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
A constant-time optimal parallel string-matching algorithm
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
An introduction to parallel algorithms
An introduction to parallel algorithms
Two-dimensional pattern matching by sampling
Information Processing Letters
Let sleeping files lie: pattern matching in Z-compressed files
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
Linear Algorithm for Data Compression via String Matching
Journal of the ACM (JACM)
Experiments in text file compression
Communications of the ACM
Efficient string matching: an aid to bibliographic search
Communications of the ACM
Implementation of the substring test by hashing
Communications of the ACM
Efficient randomized pattern-matching algorithms
IBM Journal of Research and Development - Mathematics and computing
Tighter bounds on the exact complexity of string matching
SFCS '92 Proceedings of the 33rd Annual Symposium on Foundations of Computer Science
SFCS '93 Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science
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We present the first known case of one-dimensional and two-dimensional string matching algorithms for text with bounded entropy. Let n be the length of the text and m be the length of the pattern. We show that the expected complexity of the algorithms is related to the entropy of the text for various assumptions of the distribution of the pattern. For the case of uniformly distributed patterns, our one dimensional matching algorithm works in O(nlogm/(pm)) expected running time where H is the entropy of the text and p=1-(1-H/sup 2/)/sup H/(1+H)/. The worst case running time T can also be bounded by (n log m/p(m+/spl radic/V))/spl les/T/spl les/(n log m/p(m-/spl radic/V)) if V is the variance of the source from which the pattern is generated. Our algorithm utilizes data structures and probabilistic analysis techniques that are found in certain lossless data compression schemes.