Chiou-Ting Tseng

Efficient algorithms for the longest common subsequence problem with sequential substring constraints

In this paper, we generalize the inclusion constrained longest common subsequence (CLCS) problem to the hybrid CLCS problem which is the combination of the sequence inclusion CLCS and the string inclusion CLCS, called the sequential sub string constrained longest common subsequence (SSCLCS) problem. In the SSCLCS problem, we are given two strings A and B of lengths m and n, respectively, formed by alphabet \Sigma and a constraint sequence C formed by ordered strings (C^1, C^2, C^3, C^l) with total length r. We are to find the longest common subsequence D of A and B containing C^1,C^2,C^3,C^l as sub strings and the order of C¡¦s are retained. This problem have two variants that the strings in C may or may not overlap. We proposed algorithms with O(mnl + (m+ n)(|\Sigma| + r)) and O(mnr + (m+ n)|\Sigma| ) time for the two variants of the problem. For the special case with one or two constraints, our algorithms runs in O(mn+(m+n)(|\Sigma| +r)) and O(mnr +(m+n)j|\Sigma|) time, which are an order faster than the algorithm proposed by Chen and Chao [1].

Efficient polynomial-time algorithms for the constrained LCS problem with strings exclusion

In this paper, we revisit a recent variant of the longest common subsequence (LCS) problem, the string-excluding constrained LCS (STR-EC-LCS) problem, which was first addressed by Chen and Chao (J Comb Optim 21(3):383–392, 2011). Given two sequences

Minimum Height and Sequence Constrained Longest Increasing Subsequence

X

Prediction of Protein Essentiality by the Support Vector Machine with Statistical Tests

and

A fast and simple algorithm for computing the longest common subsequence of run-length encoded strings

Y

Fast algorithms for computing the constrained LCS of run-length encoded strings

of lengths