Efficient merged longest common subsequence algorithms for similar sequences
Autor: | Chang-Biau Yang, Kuo-Tsung Tseng, De-Sheng Chan, Shou-Fu Lo |
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Rok vydání: | 2018 |
Předmět: |
Sequence
General Computer Science 0102 computer and information sciences 02 engineering and technology Longest increasing subsequence Space (mathematics) 01 natural sciences Theoretical Computer Science Longest common subsequence problem 010201 computation theory & mathematics Longest alternating subsequence Subsequence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Time complexity Algorithm Mathematics Web site |
Zdroj: | Theoretical Computer Science. 708:75-90 |
ISSN: | 0304-3975 |
DOI: | 10.1016/j.tcs.2017.10.027 |
Popis: | Given a pair of merging sequences A, B and a target sequence T, the merged longest common subsequence (MLCS) problem is to find out the longest common subsequence (LCS) between sequences E ( A , B ) and T, where E ( A , B ) is obtained from merging two subsequences of A and B. In this paper, we first propose an algorithm for solving the MLCS problem in O ( n | Σ | + ( r − L + 1 ) L m ) time and O ( n | Σ | + L m ) space, where r and L denote the lengths of T and MLCS, respectively, and m and n denote the shorter and longer lengths of A and B, respectively. From the time complexity, it is clear that our algorithm is very efficient when T and E ( A , B ) are very similar. With slight modification, our algorithm can also solve another merged LCS problem variant, the block-merged LCS (BMLCS) problem, in O ( n | Σ | + ( r − L + 1 ) L δ ) time and O ( n | Σ | + L δ ) space, where δ denotes the larger number of blocks of A and B. Experimental results show that our algorithms are faster than other previously published MLCS and BMLCS algorithms for sequences with high similarities. The source codes and datasets for experiments can be found on our web site http://par.cse.nsysu.edu.tw/~mlcs/ [20] . |
Databáze: | OpenAIRE |
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