An improved algorithm for computing the edit distance of run-length coded strings
Information Processing Letters
Matching for run-length encoded strings
Journal of Complexity
The String-to-String Correction Problem
Journal of the ACM (JACM)
Algorithms for the Longest Common Subsequence Problem
Journal of the ACM (JACM)
The Complexity of Some Problems on Subsequences and Supersequences
Journal of the ACM (JACM)
A fast algorithm for computing longest common subsequences
Communications of the ACM
LATIN '00 Proceedings of the 4th Latin American Symposium on Theoretical Informatics
The constrained longest common subsequence problem
Information Processing Letters
Information Processing Letters
A simple algorithm for the constrained sequence problems
Information Processing Letters
Regular expression constrained sequence alignment
Journal of Discrete Algorithms
New efficient algorithms for the LCS and constrained LCS problems
Information Processing Letters
The SBC-tree: an index for run-length compressed sequences
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Finding the longest common subsequence for multiple biological sequences by ant colony optimization
Computers and Operations Research
Information Processing Letters
Beam search for the longest common subsequence problem
Computers and Operations Research
On the generalized constrained longest common subsequence problems
Journal of Combinatorial Optimization
| Hi-index | 5.23 |
The constrained LCS (CLCS) problem, a recent variant of the longest common subsequence (LCS) problem, has gained much attention. Given two sequences X and Y of lengths n and m, respectively, and the constrained sequence P of length r, previous research shows that the CLCS problem can be solved by either an O(nmr)-time algorithm based upon dynamic programming (DP) techniques or an O(rRloglog(n+m))-time Hunt-Szymanski-like algorithm, where R is the total number of ordered pairs of positions at which the two strings match. In this paper, we investigate the case that X, Y and P are all in run-length encoded (RLE) format, where the numbers of runs are N, M and R, respectively. We first show that when the sequences are encoded, the CLCS problem can be solved by a simple algorithm in O(nmR+nMr+Nmr) time without decompressing the sequences. Then, we propose a more efficient algorithm with O(NMr+rxmin{q"1,q"2}+q"3) time, where q"1 and q"2 denote the numbers of elements in the south and east faces of the matched blocks on the first layer, respectively, and q"3 denotes the number of face elements of all fully matched cuboids in the DP lattice.