A matching in a graph is a set of edges no two of which share a common vertex. A matching M is an induced matching if no edge connects two edges of M. The problem of finding a maximum induced matching is known to be N...
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A matching in a graph is a set of edges no two of which share a common vertex. A matching M is an induced matching if no edge connects two edges of M. The problem of finding a maximum induced matching is known to be NP-Complete in general-and specifically for bipartite graphs and for 3-regular planar graphs. The problem has been shown to be polynomial for several classes of graphs. In this paper we generalize the results to:wider classes of graphs, and improve the time complexity of previously known results. (C) 2000 Elsevier Science B.V. All rights reserved.
Let a text string T of n symbols and a pattern string P of m symbols from alphabet Sigma be given. A swapped version T' of T is a length n string derived from T by a series of local swaps (i.e., t(l)' <-- t...
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Let a text string T of n symbols and a pattern string P of m symbols from alphabet Sigma be given. A swapped version T' of T is a length n string derived from T by a series of local swaps (i.e., t(l)' <-- t(l+1) and t(l+1)' <-- t(l)), where each element can participate in no more than one swap. The pattern matching with swaps problem is that of finding all locations i for which there exists a swapped version T' of T with an exact matching of P in location i of T'. It has been an open problem whether swapped matching can be done in less than O(nm) time. In this paper we show the first algorithm that solves the pattern matching with swaps problem in time o(nm). We present an algorithm whose time complexity is O(nm(1/3) log m log sigma) for a general alphabet Sigma, where sigma = min(m, \Sigma\). (C) 2000 Academic Press.
The importance of hypertext has been steadily growing over the past decade. The Internet and other information systems use hypertext formal, with data organized associatively rather than sequentially or relationally. ...
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The importance of hypertext has been steadily growing over the past decade. The Internet and other information systems use hypertext formal, with data organized associatively rather than sequentially or relationally. A myriad of textual problems have been considered in the pattern matching field with many nontrivial results. Nevertheless, surprisingly little work has been done on the natural combination ol pattern matching and hypertext. Ln contrast to regular text, hypertext has a nonlinear structure and the techniques of pattern matching for text cannot be directly applied to hypertext. Manber and Wu (1992, "IAPR Workshop on Structural and Syntactic Pattern Recognition, Bern, Switzerland) pioneered the study of pattern matching in hypertext and defined a hypertext model for pattern matching. Akutsu (1993, "Procedures of the 4th Symposium on Combinatorial Pattern Matching Podova, Italy," pp. 1-10) developed an algorithm that can be used for exact pattern matching in a tree-structured hypertext. Park and I(im (1995, "6th Symposium on Combinatorial Pattern Matching;Helsinki, Finland") considered regular pattern matching in hypertext. They developed a complex algorithm that works for hypertext with an underlying structure of a DAG. In this paper we present a much simpler algorithm achieving the same complexity which runs on any hypertext graph. We then extend the problem to approximate pattern matching in hypertext, first considering hamming distance and then edit distance. We show that in contrast to regular text, it dos make a difference whether Che;errors occur in the hypertext or the pattern The approximate pattern matching problem in hypertext with errors in the hypertext turns out to be NP-complete anti the approximate pattern matching problem in hypertext: with errors in the pattern has a polynomial time solution, (C) 2000 Academic Press.
Let a text string T of n symbols and a pattern string P of rn symbols from alphabet Sigma be given. A swapped version P' of P is a length m string derived from P by a series of local swaps, (i.e. p'(l) <-- ...
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ISBN:
(数字)9783540444503
ISBN:
(纸本)3540414134
Let a text string T of n symbols and a pattern string P of rn symbols from alphabet Sigma be given. A swapped version P' of P is a length m string derived from P by a series of local swaps, (i.e. p'(l) <-- p(l+1) and p'(l+1) <-- p(l)) where each element can participate in no more than one swap. The Pattern Matching with Swaps problem is that of finding all locations i of T for which there exists a swapped version P' of P with an exact matching of P' in location i of T. Recently, some efficient algorithms were developed for this problem. Their time complexity is better than the best known algorithms for pattern matching with mismatches. However, the Approximate Pattern Matching with Swaps problem was not known to be solved faster than the pattern matching with mismatches problem. In the Approximate Pattern Matching with Swaps problem the output is, for every text location i where there is a swapped match of P, the number of swaps necessary to create the swapped version that matches location i. The fastest known method to-date is that of counting mismatches and dividing by two. The time complexity of this method is O(n rootm log m) for a general alphabet Sigma. In this paper we show an algorithm that counts the number of swaps at every location where there is a swapped matching in time O(n log m log sigma), where sigma = min(m, \Sigma\). Consequently, the total time for solving the approximate pattern matching with swaps problem is O(f(n, m) + n log m log a), where f (n, m) is the time necessary for solving the pattern matching with swaps problem.
We study the parameterized complexity of three NP-hard graph completion problems. The minimum fill-in problem asks if a graph can be triangulated by adding at most k edges. We develop O(c(k)m) and O(k(2)mn + f(k)) alg...
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We study the parameterized complexity of three NP-hard graph completion problems. The minimum fill-in problem asks if a graph can be triangulated by adding at most k edges. We develop O(c(k)m) and O(k(2)mn + f(k)) algorithms for this problem on a graph with n vertices and m edges. Here f(k) is exponential in k and the constants hidden by the big-O notation are small and do not depend on k. In particular, this implies that the problem is fixed-parameter tractable (FPT). The proper interval graph completion problem, motivated by molecular biology, asks if a graph can be made proper interval by adding no more than k edges. We show that the problem is FPT by providing a simple search-tree-based algorithm that solves it in O(c(k)m)-time. Similarly, we show that the parameterized version of the strongly chordal graph completion problem is FPT by giving an O(c(k)m log n)-time algorithm for it. All of our algorithms can actually enumerate all possible k-completions within the same time bounds.
The problems of Interval Sandwich (IS)and Intervalizing Colored Graphs' (ICG) have received a lot of attention recently, due to their applicability to DNA physical mapping problems with ambiguous data. Most of the...
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The problems of Interval Sandwich (IS)and Intervalizing Colored Graphs' (ICG) have received a lot of attention recently, due to their applicability to DNA physical mapping problems with ambiguous data. Most of the results obtained so far on the problems were hardness results. Here we study the problems under assumptions of sparseness, which hold in the biological context. We prove that both problems are polynomial when either (1) the input graph degree and the solution graph clique size are bounded, or (2) the solution graph degree is bounded. In particular, this implies that ICC is polynomial on bounded degree graphs for every fixed number of colors, in contrast with the recent result of Bodlaender and de Fluiter.
Generation of all maximal independent sets (MIS) is a NP-complete problem for general graphs. In this paper, using a particular geometric property of trapezoid graph, an efficient algorithm is designed which enables t...
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Generation of all maximal independent sets (MIS) is a NP-complete problem for general graphs. In this paper, using a particular geometric property of trapezoid graph, an efficient algorithm is designed which enables to generate an maximal independent sets for a trapezoid graph in O(n (m) over bar + alpha n) time, where (m) over bar and alpha are respectively the number of edges of the complement graph of the given graph and the number of generated maximal independent sets. There is no prior algorithm available to solve this problem of finding all MIS for trapezoid graphs.
This paper looks at the complexity of four different incremental problems. The following are the problems considered: (1) Interval partitioning of a flow graph (2) Breadth first search (BFS) of a directed graph (3) Le...
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This paper looks at the complexity of four different incremental problems. The following are the problems considered: (1) Interval partitioning of a flow graph (2) Breadth first search (BFS) of a directed graph (3) Lexicographic depth first search (DFS) of a directed graph (4) Constructing the postorder listing of the nodes of a binary tree. The last problem arises out of the need for incrementally computing the Sethi-Ullman (SU) ordering [1] of the subtrees of a tree after it has undergone changes of a given type. These problems are among those that claimed our attention in the process of our designing algorithmic techniques for incremental code generation. BFS and DFS have certainly numerous other applications, but as far as our work is concerned, incremental code generation is the common thread linking these problems. The study of the complexity of these problems is done from two different perspectives. In [2] is given the theory of incremental relative lower bounds (IRLB). We use this theory to derive the IRLBs of the first three problems. Then we use the notion of a bounded incremental algorithm [4] to prove the unboundedness of the fourth problem with respect to the locally persistent model of computation. Possibly, the lower bound result for lexicographic DFS is the most interesting. In [5] the author considers lexicographic DFS to be a problem for which the incremental version may require the recomputation of the entire solution from scratch. In that sense, our IRLB result provides further evidence for this possibility with the proviso that the incremental DFS algorithms considered be ones that do not require too much of preprocessing.
We carry out an experimental analysis of a number of shortest-path (routing) algorithms investigated in the context of the TRANSIMS (TRansportation analysis and SIMulation System) project. The main focus of the paper ...
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We study some minimum-area hull problems that generalize the notion of convex hull to starshaped and monotone hulls. Specifically, we consider the minimum-area star-shaped hull problem: Given an n-vertex simple polygo...
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We study some minimum-area hull problems that generalize the notion of convex hull to starshaped and monotone hulls. Specifically, we consider the minimum-area star-shaped hull problem: Given an n-vertex simple polygon P, find a minimum-area, star-shaped polygon P* containing P. This problem arises in lattice packings of translates of multiple, nonidentical shapes in material layout problems (e.g., in clothing manufacture), and has been recently posed by Daniels and Milenkovic. We consider two versions of the problem: the restricted version, in which the vertices of P* are constrained to be vertices of P, and the unrestricted version, in which the vertices of P* can be anywhere in the plane. We prove that the restricted problem falls in the class of "3SUM-hard" (sometimes called "n(2)-hard") problems, which are suspected to admit no solutions in o(n(2)) time. Further, we give an O(n(2)) time algorithm, improving the previous bound of O(n(5)). We also show that the unrestricted problem can be solved in O(n(2)p(n)) time, where p(n) is the time needed to find the roots of two equations in two unknowns, each a polynomial of degree O (n). We also consider the case in which P* is required to be monotone, with respect to an unspecified direction;we refer to this as the minimum-area monotone hull problem. We give a matching lower and upper bound of O (n log n) time for computing P* in the restricted version, and an upper bound of O (nq(n)) time in the unrestricted version, where q(n) is the time needed to find the roots of two polynomial equations in two unknowns with degrees 2 and O(n).
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