AbstractAn approximation algorithm for the shortest common superstring problem is developed, based on the Knuth-Morris-Pratt string-matching procedure and on the greedy heuristics for finding longest Hamiltonian paths in weighted graphs. Given a set R of strings, the algorithm constructs a common superstring for R in O(mn) steps where m is the number of strings in R and n is the total length of these strings. The performance of the algorithm is analysed in terms of the compression in the common superstrings constructed, that is, in terms of n−k where k is the length of the obtained superstring. We show that (n−k)⩾12(n−kmin) where kmin is the length of a shortest common superstring. Hence the compression achieved by the algorithm is at least...
(SACS) problem is: Given a set of strings f={w 1, w 2, … , w n}, where no w i is an approximate sub...
The Shortest Approximate Common Superstring (SACS) problem is : Given a set of strings f={w1, w2, .....
. Superstrings have many applications in data compression and genetics. However the decision version...
AbstractAn approximation algorithm for the shortest common superstring problem is developed, based o...
Abstract. An approximation algorithm for the shortest common superstring problem is developed, based...
AbstractThe object of the shortest common superstring problem (SCS) is to find the shortest possible...
In the Shortest Common Superstring (SCS) problem, one is given a collection of strings, and needs to...
We study a variation of the classical Shortest Common Superstring (SCS) problem in which a shortest ...
Given a set of strings, the shortest common superstring problem is to find the shortest possible str...
AbstractGiven a collection of strings ifS = s1, …, sn over an alphabet ∑, a superstring α of S is a ...
In the Shortest Superstring problem (SS) one has to find a shortest string s containing given string...
The objective of the shortest common superstring problem is to find a string of minimum length that ...
AbstractVarious versions of the shortest common superstring problem play important roles in data com...
AbstractMerging words according to their overlap yields a superstring. This basic operation allows t...
Given a collection of strings S={s_1, ..., s_n} over an alphabet \Sigma, a superstring \alpha of S i...
(SACS) problem is: Given a set of strings f={w 1, w 2, … , w n}, where no w i is an approximate sub...
The Shortest Approximate Common Superstring (SACS) problem is : Given a set of strings f={w1, w2, .....
. Superstrings have many applications in data compression and genetics. However the decision version...
AbstractAn approximation algorithm for the shortest common superstring problem is developed, based o...
Abstract. An approximation algorithm for the shortest common superstring problem is developed, based...
AbstractThe object of the shortest common superstring problem (SCS) is to find the shortest possible...
In the Shortest Common Superstring (SCS) problem, one is given a collection of strings, and needs to...
We study a variation of the classical Shortest Common Superstring (SCS) problem in which a shortest ...
Given a set of strings, the shortest common superstring problem is to find the shortest possible str...
AbstractGiven a collection of strings ifS = s1, …, sn over an alphabet ∑, a superstring α of S is a ...
In the Shortest Superstring problem (SS) one has to find a shortest string s containing given string...
The objective of the shortest common superstring problem is to find a string of minimum length that ...
AbstractVarious versions of the shortest common superstring problem play important roles in data com...
AbstractMerging words according to their overlap yields a superstring. This basic operation allows t...
Given a collection of strings S={s_1, ..., s_n} over an alphabet \Sigma, a superstring \alpha of S i...
(SACS) problem is: Given a set of strings f={w 1, w 2, … , w n}, where no w i is an approximate sub...
The Shortest Approximate Common Superstring (SACS) problem is : Given a set of strings f={w1, w2, .....
. Superstrings have many applications in data compression and genetics. However the decision version...