A new technique for compression and storage of data
Communications of the ACM
Common phrases and minimum-space text storage
Communications of the ACM
Communications of the ACM
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Data compression via textual substitution
Journal of the ACM (JACM)
Is text compression by prefixes and suffixes practical?
SIGIR '82 Proceedings of the 5th annual ACM conference on Research and development in information retrieval
Repetition Complexity of Words
COCOON '02 Proceedings of the 8th Annual International Conference on Computing and Combinatorics
Overlap in Adaptive Vector Quantization
DCC '01 Proceedings of the Data Compression Conference
A fully linear-time approximation algorithm for grammar-based compression
CPM'03 Proceedings of the 14th annual conference on Combinatorial pattern matching
Approximability of minimum AND-Circuits
SWAT'06 Proceedings of the 10th Scandinavian conference on Algorithm Theory
Improving time and space complexity for compressed pattern matching
ISAAC'06 Proceedings of the 17th international conference on Algorithms and Computation
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A general model for data compression is presented which includes most data compression systems in the literature as special cases. All macro schemes are based on the principle of finding redundant strings or patterns and replacing them by pointers to a common copy. Different varieties of macro schemes may be defined by varying the interpretation of pointers, for instance, a pointer may indicate a substring of the compressed string, a substring of the original string, or a substring of some other string such as an external dictionary. Other varieties of macros schemes may be defined by restricting the type of overlapping or recursion that may be used. Trade-offs between different varieties of macro schemes, exact lower bounds on the amount of compression obtainable, and the complexity of encoding and decoding are discussed as well as how the work of other authors (such as Lempel-Ziv) relates to this model.