The longest letter-duplicated subsequence and related problems
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Published:2024-07-20
Issue:3
Volume:61
Page:315-329
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ISSN:0001-5903
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Container-title:Acta Informatica
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language:en
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Short-container-title:Acta Informatica
Author:
Lai Wenfeng,Liyanage Adiesha,Zhu Binhai,Zou Peng
Abstract
AbstractMotivated by computing duplication patterns in sequences, a new problem called the longest letter-duplicated subsequence (LLDS) is proposed. Given a sequence S of length n, a letter-duplicated subsequence is a subsequence of S in the form of $$x_1^{d_1}x_2^{d_2}\ldots x_k^{d_k}$$
x
1
d
1
x
2
d
2
…
x
k
d
k
with $$x_i\in \Sigma $$
x
i
∈
Σ
, $$x_j\ne x_{j+1}$$
x
j
≠
x
j
+
1
and $$d_i\ge 2$$
d
i
≥
2
for all i in [k] and j in $$[k-1]$$
[
k
-
1
]
. A linear time algorithm for computing a longest letter-duplicated subsequence (LLDS) of S can be easily obtained. In this paper, we focus on two variants of this problem: (1) ‘all-appearance’ version, i.e., all letters in $$\Sigma $$
Σ
must appear in the solution, and (2) the weighted version. For the former, we obtain dichotomous results: We prove that, when each letter appears in S at least 4 times, the problem and a relaxed version on feasibility testing (FT) are both NP-hard. The reduction is from $$(3^+,1,2^-)$$
(
3
+
,
1
,
2
-
)
-SAT, where all 3-clauses (i.e., containing 3 lals) are monotone (i.e., containing only positive literals) and all 2-clauses contain only negative literals. We then show that when each letter appears in S at most 3 times, then the problem admits an O(n) time algorithm. Finally, we consider the weighted version, where the weight of a block $$x_i^{d_i} (d_i\ge 2)$$
x
i
d
i
(
d
i
≥
2
)
could be any positive function which might not grow with $$d_i$$
d
i
. We give a non-trivial $$O(n^2)$$
O
(
n
2
)
time dynamic programming algorithm for this version, i.e., computing an LD-subsequence of S whose weight is maximized.
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Reference23 articles.
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