Mismatch Sampling

Raphaël Clifford, Klim Efremenko, Benny Porat, Ely Porat, Amir Rothschild

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


We consider the well known problem of pattern matching under the Hamming distance. Previous approaches have shown how to count the number of mismatches efficiently, especially when a bound is known for the maximum Hamming distance. Our interest is different in that we wish collect a random sample of mismatches of fixed size at each position in the text. Given a pattern p of length m and a text t of length n, we show how to sample with high probability c mismatches where possible from every alignment of p and t in O((cthinspace+thinspacelogn)(nthinspace+thinspacemlogm)logm) time. Further, we guarantee that the mismatches are sampled uniformly and can therefore be seen as representative of the types of mismatches that occur.
Original languageEnglish GB
Title of host publicationString Processing and Information Retrieval
EditorsAmihood Amir, Andrew Turpin, Alistair Moffat
Place of PublicationBerlin, Heidelberg
Number of pages10
ISBN (Print)978-3-540-89097-3
StatePublished - 2009
Externally publishedYes
Event15th International Symposium on String Processing and Information Retrieval, SPIRE 2008 - Melbourne. VIC, Australia
Duration: 10 Nov 200812 Nov 2008

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
ISSN (Print)0302-9743


Conference15th International Symposium on String Processing and Information Retrieval, SPIRE 2008
CityMelbourne. VIC

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)


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