> \pJava Excel API v2.6 Ba==h\:#8X@"1Arial1Arial1Arial1Arial + ) , * `DC,title[*]contributor[author]contributor[advisor]keywords[*]date[issued] publisher citationsidentifier[uri]identifier[doi]abstractrelation[journal]relation[volume]relation[no]relation[page]>Suffix Tree of Alignment: An Efficient Index for Similar Data.l3Indexes for similar data;
suffix trees;
alignments;2013-07SPRINGER-VERLAG8Lecture Notes in Computer Science, 2013, 8288, P.337-348khttps://link.springer.com/chapter/10.1007%2F978-3-642-45278-9_29;
http://hdl.handle.net/20.500.11754/52109;10.1007/978-3-642-45278-9_29?We 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.337-348&HQsj&)KLng'03zA3U
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