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Suffix tree of alignment: An efficient index for similar data

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dc.contributor.authorNa, Joong Chae-
dc.contributor.authorPark, Heejin-
dc.contributor.authorCrochemore, Maxime-
dc.contributor.authorHolub, Jan-
dc.contributor.authorIliopoulos, Costas S.-
dc.contributor.authorMouchard, Laurent-
dc.contributor.authorPark, Kunsoo-
dc.date.accessioned2022-07-16T09:07:29Z-
dc.date.available2022-07-16T09:07:29Z-
dc.date.created2021-05-13-
dc.date.issued2013-07-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/162359-
dc.description.abstractWe consider an index data structure for similar strings. The generalized suffix tree can be a solution for this. The generalized suffix tree of two strings A and B is a compacted trie representing all suffixes in A and B. It has |A| + |B| leaves and can be constructed in O(|A| + |B|) time. However, if the two strings are similar, the generalized suffix tree is not efficient because it does not exploit the similarity which is usually represented as an alignment of A and B. In this paper we propose a space/time-efficient suffix tree of alignment which wisely exploits the similarity in an alignment. Our suffix tree for an alignment of A and B has |A| + l d + l 1 leaves where l d is the sum of the lengths of all parts of B different from A and l 1 is the sum of the lengths of some common parts of A and B. We did not compromise the pattern search to reduce the space. Our suffix tree can be searched for a pattern P in O(|P| + occ) time where occ is the number of occurrences of P in A and B. We also present an efficient algorithm to construct the suffix tree of alignment. When the suffix tree is constructed from scratch, the algorithm requires O(|A| + l d + l 1 + l 2) time where l 2 is the sum of the lengths of other common substrings of A and B. When the suffix tree of A is already given, it requires O(l d + l 1 + l 2) time.-
dc.language영어-
dc.language.isoen-
dc.publisherSpringer Verlag-
dc.titleSuffix tree of alignment: An efficient index for similar data-
dc.typeArticle-
dc.contributor.affiliatedAuthorPark, Heejin-
dc.identifier.doi10.1007/978-3-642-45278-9_29-
dc.identifier.scopusid2-s2.0-84893109534-
dc.identifier.bibliographicCitationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.8288 LNCS, pp.337 - 348-
dc.relation.isPartOfLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.citation.titleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.citation.volume8288 LNCS-
dc.citation.startPage337-
dc.citation.endPage348-
dc.type.rimsART-
dc.type.docTypeConference Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusIndex data structures-
dc.subject.keywordPlusPattern search-
dc.subject.keywordPlusSimilar datum-
dc.subject.keywordPlusSub-strings-
dc.subject.keywordPlusSuffix-trees-
dc.subject.keywordPlusAlgorithms-
dc.subject.keywordPlusAlignment-
dc.subject.keywordPlusCombinatorial mathematics-
dc.subject.keywordPlusForestry-
dc.subject.keywordPlusTrees (mathematics)-
dc.subject.keywordPlusAlgorithms-
dc.subject.keywordPlusForestry-
dc.subject.keywordPlusMathematics-
dc.subject.keywordPlusTrees-
dc.subject.keywordAuthoralignments-
dc.subject.keywordAuthorIndexes for similar data-
dc.subject.keywordAuthorsuffix trees-
dc.identifier.urlhttps://link.springer.com/chapter/10.1007/978-3-642-45278-9_29-
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