Approximate string-matching with q-grams and maximal matches
Theoretical Computer Science - Selected papers of the Combinatorial Pattern Matching School
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Efficient search for approximate nearest neighbor in high dimensional spaces
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Lower bounds for high dimensional nearest neighbor search and related problems
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
The String-to-String Correction Problem
Journal of the ACM (JACM)
A guided tour to approximate string matching
ACM Computing Surveys (CSUR)
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Locality-sensitive hashing scheme based on p-stable distributions
SCG '04 Proceedings of the twentieth annual symposium on Computational geometry
Approximating Edit Distance Efficiently
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
A Binding Procedure for Distributed Binary Data Representations
Cybernetics and Systems Analysis
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A method is proposed for approximation of the classic edit distance between strings. The method is based on a mapping of strings into vectors belonging to a space with an easily calculable metric. The method preserves the closeness of strings and makes it possible to accelerate the computation of edit distances. The developed q-gram method of approximation of edit distances and its two randomized versions improves the approximation quality in comparison with well-known results.