| Summary: | 碩士 === 國立暨南國際大學 === 資訊工程學系 === 94 === In this thesis, we address the constrained longest common subsequence problem
which is defined as follows. Given two sequences X and Y, and a constrained sequence Z,
find a longest common subsequence P of X and Y such that Z is a subsequence of P.
Recently, Chin and other four authors [CSFHK2004] proposed an O(nmr) time and
space algorithm to solve this problem using the dynamic programming technique, where n,
m and r are the lengths of X, Y and Z, respectively. By reviewing Chin’s method, we
found that many computations in Chin’s method can be ignored.
In this thesis, we present an algorithm to solve the constrained longest common
subsequence problem in O(nmr) time and space also. But, our method runs faster than
Chin’s method because fewer computations are need in our method. In addition, less
memory space is needed in our method.
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