Rick, C.: A new flexible algorithm for the longest common subsequence problem. Proceedings, 6th Annual Symp. on Combinatorial Pattern Matching, LNCS 937, 1995, 340--351.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... (u[i] v[j] 1 i; j n where (u[i] v[j] is defined as 1 if both characters are equal, or 0 otherwise. The length of the LCS is given by L[n; n] This algorithm can be implemented using only 2n comparisons. For faster algorithms which solve the LCS we refer the reader to [GBY91, PD94, Ric95] Longest Common Forests (LCF) are defined in [PW93] as one particular case of general alignments between strings, called the A LCS problem. Basically, in a LCF we allow a character to match more than one character of the other sequence, but if we look at every match as an edge between the two ....

Claus Rick. A new flexible algorithm for the longest common subsequence problem. In CPM'95, 6th Annual Symposium on Combinatorial Pattern Matching, Lecture Notes in Computer Science 937, pages 340--351, Espoo, Finland, 1995. Springer-Verlag. This article was processed using the L A T E X 2 " macro package with CUP CS class

.... the interest for finding e#cient algorithms for it is mainly in the framework of molecular biology (the lcs is commonly used as a measure of similarity in the analysis of biological sequences [19] The problem of computing the lcs of two sequences has been deeply investigated (see the survey in [15]) and a number of algorithms have been proposed in order to improve the running time for typical instances [2,16,10,17] but all these algorithms still have a O(n ) time complexity in the worst case. The only algorithm that has broken this barrier is the one by Masek and Paterson [14] based on ....

C. Rick. A new flexible algorithm for the longest common subsequence problem.

....processor cycles to reduce the amount of data transferred. This technology can be used to provide backup and restore services on a subscription basis over any network including the Internet. 4 1. 3 Previous Work Differencing has it origins in both longest common subsequence (LCS) algorithms [3, 12] and the string to string correction problem [17] Some of the first applications of differencing updated the screens of slow terminals by sending a set of edits to be applied locally rather than retransmitting a screen full of data. Another early application was the UNIX diff utility which used ....

RICK, C. A new flexible algorithm for the longest common subsequence problem. In Proceedings of the 6th Annual Symposium on Combinatorial Patterm Matching Espoo, Finland, 5-7 July 1995 (1995). 61

....(u[i] v[j] 1 i; j n ; where (u[i] v[j] is defined as 1 if both letters are equal, or 0 otherwise. The length of the LCS is given by L[n; n] This algorithm can be implemented using 3n 2 comparisons. For faster algorithms which solve the LCS problem we refer the reader to [GBY91, PD94, Ric95] Longest Common Forests (LCF) are defined in [PW93] as one particular case of general alignments between strings, called the A LCS problem. Basically, in a LCF we allow a letter to match more than one letter of the other sequence, but if we look at every match as an edge between the two ....

Claus Rick. A new flexible algorithm for the longest common subsequence problem. In CPM'95, 6th Annual Symposium on Combinatorial Pattern Matching, Lecture Notes in Computer Science 937, pages 340--351, Espoo, Finland, 1995. Springer-Verlag.

....Hence a problem that is related to both the ordered tree inclusion problem and the tree editing problem is the problem of determining the largest common substructure of two trees. The latter problem is an extension of the well known longest common subsequence problem (see [4] 5] 1] and [16], for example) to trees. Here one seeks for the largest common substructure of two ordered labeled trees T 1 and T 2 that can be obtained by deleting nodes from T 1 and T 2 in the sense of the tree editing problem. This problem can be solved by an algorithm for the tree editing problem by a ....

C. Rick, A New Flexible Algorithm for the Longest Common Subsequence Problem, Nordic J. Comput. 2 (1995), pp. 444 - 461.

.... (u[i] v[j] 1 i; j n where (u[i] v[j] is defined as 1 if both characters are equal, or 0 otherwise. The length of the LCS is given by L[n; n] This algorithm can be implemented using only 2n 2 comparisons. For faster algorithms which solve the LCS we refer the reader to [GBY91, PD94, Ric95] Longest Common Forests (LCF) are defined in [PW93] as one particular case of general alignments between strings, called the A LCS problem. Basically, in a LCF we allow a character to match more than one character of the other sequence, but if we look at every match as an edge between the two ....

Claus Rick. A new flexible algorithm for the longest common subsequence problem. In CPM'95, 6th Annual Symposium on Combinatorial Pattern Matching, Lecture Notes in Computer Science 937, pages 340--351, Espoo, Finland, 1995. Springer-Verlag. This article was processed using the L A T E X 2 " macro package with CUP CS class

....= v[j] 1 i; j n ; where (u[i] v[j] is defined as 1 if both characters are equal, or 0 otherwise. The length of the LCS is given by L[n; n] This algorithm can be implemented using 3n 2 comparisons. For faster algorithms which solve the LCS problem we refer the reader to [GBY91, PD94, Ric95] Longest Common Forests (LCF) are defined in [PW93] as one particular case of general alignments between strings, called the A LCS problem. Basically, in a LCF we allow a character to match more than one character of the other sequence, but if we look at every match as an edge between the two ....

Claus Rick. A new flexible algorithm for the longest common subsequence problem. In CPM'95, 6th Annual Symposium on Combinatorial Pattern Matching, Lecture Notes in Computer Science 937, pages 340--351, Espoo, Finland, 1995. Springer-Verlag.

.... [1975] they are improved in Johnson [1982] Modifications to the Hunt Szymanski algorithm are discussed in Hsu and Du [1984a] but see Apostolico [1987] Apostolico and Guerra [1987] and Eppstein, Galil, Giancarlo, and Italiano [1990] Other algorithms are discussed in Chin and Poon [1990] and Rick [1995]. The O(nD) time algorithm is due to Nakatsu, Kambayashi, and Yajima [1982] The code in Figure 4.7 is from their paper, with changes in the variable names. The linear space version of Nakatsu s algorithm is shown in Kumar and Rangan [1987] Myers algorithm is from Myers [1986] The code in Figure ....

Rick, C. [1995]. "A new flexible algorithm for the longest common subsequence problem," Proc. of the 6th Annual Symp. on Combinatorial Pattern Matching, Lecture Notes in Computer Science 937, 340-351.

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Rick, C.: A new flexible algorithm for the longest common subsequence problem. Proceedings, 6th Annual Symp. on Combinatorial Pattern Matching, LNCS 937, 1995, 340--351.

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C. Rick. A New Flexible Algorithm for the Longest Common Subsequence Problem. Technical report, University of Bonn, Computer Science Department IV, 1994.

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C. Rick. A new flexible algorithm for the longest common subsequence problem. In Proc. 6th Combinatorial Pattern Matching (CPM'95), LNCS 937, pages 340--351, 1995.

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C. Rick. A new flexible algorithm for the longest common subsequence volume 937 of LNCS, pages 340--351, 1995.

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