Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/41733
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dc.titleA linear size index for approximate pattern matching
dc.contributor.authorChan, H.-L.
dc.contributor.authorLam, T.-W.
dc.contributor.authorSung, W.-K.
dc.contributor.authorTam, S.-L.
dc.contributor.authorWong, S.-S.
dc.date.accessioned2013-07-04T08:34:27Z
dc.date.available2013-07-04T08:34:27Z
dc.date.issued2006
dc.identifier.citationChan, H.-L.,Lam, T.-W.,Sung, W.-K.,Tam, S.-L.,Wong, S.-S. (2006). A linear size index for approximate pattern matching. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4009 LNCS : 49-59. ScholarBank@NUS Repository.
dc.identifier.isbn3540354557
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41733
dc.description.abstractThis paper revisits the problem of indexing a text S[1.,n] to support searching substrings in S that match a given pattern P[1..m] with at most k errors. A naive solution either has a worst-case matching time complexity of Ω(m k) or requires Ω(n k) space. Devising a solution with better performance has been a challenge until Cole et al. [5] showed an O(nlog k n)-space index that can support k-error matching in O(m+occ+log k n log log n) time, where occ is the number of occurrences. Motivated by the indexing of DNA, we investigate in this paper the feasibility of devising a linear-size index that still has a time complexity linear in m. In particular, we give an O(n)-apace index that supports k-error matching in O(m + occ+ (log n) k(k+1) log log n) worst-case time. Furthermore, the index can be compressed from O(n) words into O(n) bits with a slight increase in the time complexity. © Springer-Verlag Berlin Heidelberg 2006.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume4009 LNCS
dc.description.page49-59
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

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