Sparse dynamic programming for longest common subsequence from fragments
BS Baker, R Giancarlo - Journal of algorithms, 2002 - Elsevier
Sparse Dynamic Programming has emerged as an essential tool for the design of efficient
algorithms for optimization problems coming from such diverse areas as computer science,
computational biology, and speech recognition. We provide a new sparse dynamic
programming technique that extends the Hunt–Szymanski paradigm for the computation of
the longest common subsequence (LCS) and apply it to solve the LCS from Fragments
problem: given a pair of strings X and Y (of length n and m, respectively) and a set M of …
algorithms for optimization problems coming from such diverse areas as computer science,
computational biology, and speech recognition. We provide a new sparse dynamic
programming technique that extends the Hunt–Szymanski paradigm for the computation of
the longest common subsequence (LCS) and apply it to solve the LCS from Fragments
problem: given a pair of strings X and Y (of length n and m, respectively) and a set M of …
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