Let sleeping files lie: pattern matching in Z-compressed files
Journal of Computer and System Sciences
String Matching with Constraints
MFCS '88 Proceedings of the Mathematical Foundations of Computer Science 1988
Efficient Algorithms for Lempel-Zip Encoding (Extended Abstract)
SWAT '96 Proceedings of the 5th Scandinavian Workshop on Algorithm Theory
Local and Global Methods in Data Mining: Basic Techniques and Open Problems
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Pattern Matching and Membership for Hierarchical Message Sequence Charts
LATIN '02 Proceedings of the 5th Latin American Symposium on Theoretical Informatics
Algorithms on Compressed Strings and Arrays
SOFSEM '99 Proceedings of the 26th Conference on Current Trends in Theory and Practice of Informatics on Theory and Practice of Informatics
A PTIME-complete matching problem for SLP-compressed words
Information Processing Letters
Fast distance multiplication of unit-Monge matrices
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Towards approximate matching in compressed strings: local subsequence recognition
CSR'11 Proceedings of the 6th international conference on Computer science: theory and applications
Faster subsequence and don't-care pattern matching on compressed texts
CPM'11 Proceedings of the 22nd annual conference on Combinatorial pattern matching
Random access to grammar-compressed strings
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Processing compressed texts: a tractability border
CPM'07 Proceedings of the 18th annual conference on Combinatorial Pattern Matching
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Given two strings (a text t of length n and a pattern p) and a natural number w, window subsequence problems consist in deciding whether p occurs as a subsequence of t and/or finding the number of size (at most) w windows of text t which contain pattern p as a subsequence, i.e. the letters of pattern p occur in the text window, in the same order as in p, but not necessarily consecutively (they may be interleaved with other letters). We are searching for subsequences in a text which is compressed using Lempel-Ziv-like compression algorithms, without decompressing the text, and we would like our algorithms to be almost optimal, in the sense that they run in time O(m) where m is the size of the compressed text. The pattern is uncompressed (because the compression algorithms are evolutive: various occurrences of a same pattern look different in the text).