Efficient string matching with k mismatches
Theoretical Computer Science
A new approach to text searching
Communications of the ACM
Surpassing the information theoretic bound with fusion trees
Journal of Computer and System Sciences - Special issue: papers from the 22nd ACM symposium on the theory of computing, May 14–16, 1990
A fast bit-vector algorithm for approximate string matching based on dynamic programming
Journal of the ACM (JACM)
A guided tour to approximate string matching
ACM Computing Surveys (CSUR)
Flexible pattern matching in strings: practical on-line search algorithms for texts and biological sequences
Approximate String Matching and Local Similarity
CPM '94 Proceedings of the 5th Annual Symposium on Combinatorial Pattern Matching
CPM '97 Proceedings of the 8th Annual Symposium on Combinatorial Pattern Matching
Fast multipattern search algorithms for intrusion detection
Fundamenta Informaticae - Special issue on computing patterns in strings
Bit-parallel string matching under Hamming distance in O(n⌈m/w⌉) worst case time
Information Processing Letters
Efficient bit-parallel algorithms for (δ, α)-matching
WEA'06 Proceedings of the 5th international conference on Experimental Algorithms
Regular expression matching with multi-strings and intervals
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
String matching with variable length gaps
SPIRE'10 Proceedings of the 17th international conference on String processing and information retrieval
String matching with variable length gaps
Theoretical Computer Science
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Many algorithms, e.g. in the field of string matching, are based on handling many counters, which can be performed in parallel, even on a sequential machine, using bit-parallelism. The recently presented technique of nested counters (Matryoshka counters ) [1] is to handle small counters most of the time, and refer to larger counters periodically, when the small counters may get full, to prevent overflow. In this work, we present several non-trivial applications of Matryoshka counters in string matching algorithms, improving their worst- or average-case time complexities. The set of problems comprises (Δ ,α )-matching, matching with k insertions, episode matching, and matching under Levenshtein distance.