dc.creatorALVES, C. E. R.
dc.creatorCACERES, E. N.
dc.creatorSONG, S. W.
dc.date.accessioned2012-10-20T04:42:50Z
dc.date.accessioned2018-07-04T15:45:55Z
dc.date.available2012-10-20T04:42:50Z
dc.date.available2018-07-04T15:45:55Z
dc.date.created2012-10-20T04:42:50Z
dc.date.issued2008
dc.identifierDISCRETE APPLIED MATHEMATICS, v.156, n.7, p.1025-1035, 2008
dc.identifier0166-218X
dc.identifierhttp://producao.usp.br/handle/BDPI/30412
dc.identifier10.1016/j.dam.2007.05.056
dc.identifierhttp://dx.doi.org/10.1016/j.dam.2007.05.056
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1627051
dc.description.abstractGiven two strings A and B of lengths n(a) and n(b), n(a) <= n(b), respectively, the all-substrings longest common subsequence (ALCS) problem obtains, for every substring B` of B, the length of the longest string that is a subsequence of both A and B. The ALCS problem has many applications, such as finding approximate tandem repeats in strings, solving the circular alignment of two strings and finding the alignment of one string with several others that have a common substring. We present an algorithm to prepare the basic data structure for ALCS queries that takes O(n(a)n(b)) time and O(n(a) + n(b)) space. After this preparation, it is possible to build that allows any LCS length to be retrieved in constant time. Some trade-offs between the space required and a matrix of size O(n(b)(2)) the querying time are discussed. To our knowledge, this is the first algorithm in the literature for the ALCS problem. (C) 2007 Elsevier B.V. All rights reserved.
dc.languageeng
dc.publisherELSEVIER SCIENCE BV
dc.relationDiscrete Applied Mathematics
dc.rightsCopyright ELSEVIER SCIENCE BV
dc.rightsrestrictedAccess
dc.subjectall substring common subsequence problem
dc.subjectstring processing
dc.titleAn all-substrings common subsequence algorithm
dc.typeArtículos de revistas


Este ítem pertenece a la siguiente institución