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93
Correspondence and translation for heterogeneous data
, 2002
"... Data integration often requires a clean abstraction of the different formats in which data are stored, and means for specifying the correspondences/relationships between data in different worlds and for translating data from one world to another. For that, we introduce in this paper a middleware dat ..."
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Cited by 77 (10 self)
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Data integration often requires a clean abstraction of the different formats in which data are stored, and means for specifying the correspondences/relationships between data in different worlds and for translating data from one world to another. For that, we introduce in this paper a middleware data model that serves as a basis for the integration task, and a declarative rules language for specifying the integration. We show that using the language, correspondences between data elements can be computed in polynomial time in many cases, andmay require exponential time only when insensitivity to order or duplicates are considered. Furthermore, we show that in most practical cases the correspondence rules can be automatically turnedinto translation rules to map data from one representation to another. Thus, a complete integration task (derivation of correspondences, transformation of data from one world to the other, incremental integration of a new bulk of data, etc.) can be specified using a single set of declarative rules.
An improved algorithm for matching large graphs
 In: 3rd IAPRTC15 Workshop on Graphbased Representations in Pattern Recognition, Cuen
, 2001
"... In this paper an improved version of a graph matching algorithm is presented, which is able to efficiently solve the graph isomorphism and graphsubgraph isomorphism problems on Attributed Relational Graphs. This version is particularly suited to work with very large graphs, since its memory require ..."
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Cited by 68 (2 self)
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In this paper an improved version of a graph matching algorithm is presented, which is able to efficiently solve the graph isomorphism and graphsubgraph isomorphism problems on Attributed Relational Graphs. This version is particularly suited to work with very large graphs, since its memory requirements are quite smaller than those of other algorithms of the same kind. After a detailed description of the algorithm, an experimental comparison is made against both the previous version (developed by the same authors) and the Ullmann’s algorithm. 1.
The Graph Isomorphism Problem
, 1996
"... The graph isomorphism problem can be easily stated: check to see if two graphs that look differently are actually the same. The problem occupies a rare position in the world of complexity theory, it is clearly in NP but is not known to be in P and it is not known to be NPcomplete. Many subdiscipli ..."
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Cited by 64 (0 self)
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The graph isomorphism problem can be easily stated: check to see if two graphs that look differently are actually the same. The problem occupies a rare position in the world of complexity theory, it is clearly in NP but is not known to be in P and it is not known to be NPcomplete. Many subdisciplines of mathematics, such as topology theory and group theory, can be brought to bear on the problem, and yet only for special classes of graphs have polynomialtime algorithms been discovered. Incongruently, this problem seems very easy in practice. It is almost always trivial to check two random graphs for isomorphism, and fast hardware implementations exists for application domains such as image processing. This paper is mostly a survey of related work in the graph isomorphism field. We examine the problem from many angles, mirroring the multifaceted nature of the literature. We survey complexity results for the graph isomorphism problem, and discuss some of the classes of graphs which hav...
Autonomous Deployment and Repair of a Sensor Network Using an Unmanned Aerial Vehicle
 in IEEE International Conference on Robotics and Automation
, 2004
"... We describe a sensor network deployment method using autonomous flying robots. Such networks are suitable for tasks such as largescale environmental monitoring or for command and control in emergency situations. We describe in detail the algorithms used for deployment and for measuring network conn ..."
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Cited by 43 (8 self)
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We describe a sensor network deployment method using autonomous flying robots. Such networks are suitable for tasks such as largescale environmental monitoring or for command and control in emergency situations. We describe in detail the algorithms used for deployment and for measuring network connectivity and provide experimental data we collected from field trials. A particular focus is on determining gaps in connectivity of the deployed network and generating a plan for a second, repair, pass to complete the connectivity. This project is the result of a collaboration between three robotics labs (CSIRO, USC, and Dartmouth.) I.
A performance comparison of five algorithms for graph isomorphism
 in Proceedings of the 3rd IAPR TC15 Workshop on Graphbased Representations in Pattern Recognition
, 2001
"... Despite the significant number of isomorphism algorithms presented in the literature, till now no efforts have been done for characterizing their performance. Consequently, it is not clear how the behavior of those algorithms varies as the type and the size of the graphs to be matched varies in case ..."
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Cited by 34 (2 self)
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Despite the significant number of isomorphism algorithms presented in the literature, till now no efforts have been done for characterizing their performance. Consequently, it is not clear how the behavior of those algorithms varies as the type and the size of the graphs to be matched varies in case of real applications. In this paper we present a benchmarking activity for characterizing the performance of a bunch of algorithms for exact graph isomorphism. To this purpose we use a large database containing 10,000 couples of isomorphic graphs with different topologies (regular graphs, randomly connected graphs, bounded valence graph), enriched with suitably modified versions of them for simulating distortions occurring in real cases. The size of the considered graphs ranges from a few nodes to about 1000 nodes. 1.
A shape analysis model with applications to a character recognition system
 IEEE Trans. Pattern Analysis and Machine Intelligence
, 1994
"... A~s~Qc~A method for the recognition of multifont printed characters is proposed, giving emphasis to the identification of structural descriptions of character shapes using prototypes. Noise and shape variations are modeled as series of transformations from groups of features in the data to features ..."
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Cited by 32 (1 self)
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A~s~Qc~A method for the recognition of multifont printed characters is proposed, giving emphasis to the identification of structural descriptions of character shapes using prototypes. Noise and shape variations are modeled as series of transformations from groups of features in the data to features in each prototype. Thus, the method manages systematically the relative distortion between a candidate shape and its prototype, accomplishing robustness to noise with less than two prototypes per class, on average. Our method uses a flexible matching between components and a flexible grouping of the individual components to be matched. A number of shape transformations are defined, including filling of gaps, so that the method handles broken characters. Also, a measure of the amount of distortion that these transformations cause is given. Classification of character shapes is defined as a minimization problem among the possible transformations that map an input shape into prototypical shapes. Some tests with handprinted numerals confirmed the method’s high robustness level. Zndex TermsShape distance, graph matching, relative neighborhood graph, broken character recognition, subgraph homeomorphism. I.
GPLAG: Detection of Software Plagiarism by Program Dependence Graph Analysis
 In the Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’06
, 2006
"... Along with the blossom of open source projects comes the convenience for software plagiarism. A company, if less selfdisciplined, may be tempted to plagiarize some open source projects for its own products. Although current plagiarism detection tools appear sufficient for academic use, they are nev ..."
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Cited by 31 (1 self)
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Along with the blossom of open source projects comes the convenience for software plagiarism. A company, if less selfdisciplined, may be tempted to plagiarize some open source projects for its own products. Although current plagiarism detection tools appear sufficient for academic use, they are nevertheless short for fighting against serious plagiarists. For example, disguises like statement reordering and code insertion can effectively confuse these tools. In this paper, we develop a new plagiarism detection tool, called GPlag, which detects plagiarism by mining program dependence graphs (PDGs). A PDG is a graphic representation of the data and control dependencies within a procedure. Because PDGs are nearly invariant during plagiarism, GPlag is more effective than stateoftheart tools for plagiarism detection. In order to make GPlag scalable to large programs, a statistical lossy filter is proposed to prune the plagiarism search space. Experiment study shows that GPlag is both effective and efficient: It detects plagiarism that easily slips over existing tools, and it usually takes a few seconds to find (simulated) plagiarism in programs having thousands of lines of code.
Computational properties of argument systems satisfying graphtheoretic constraints
 Artificial Intelligence
, 2007
"... One difficulty that arises in abstract argument systems is that many natural questions regarding argument acceptability are, in general, computationally intractable having been classified as complete for classes such as NP, coNP, and ¢¡ £. In consequence, a number of researchers have considered me ..."
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Cited by 31 (8 self)
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One difficulty that arises in abstract argument systems is that many natural questions regarding argument acceptability are, in general, computationally intractable having been classified as complete for classes such as NP, coNP, and ¢¡ £. In consequence, a number of researchers have considered methods for specialising the structure of such systems so as to identify classes for which efficient decision processes exist. In this paper the effect of a number of graphtheoretic restrictions is considered: ¤partite systems (¤¦¥¨ § ) in which the set of arguments may be partitioned into ¤ sets each of which is conflictfree; systems in which the numbers of attacks originating from and made upon any argument are bounded; planar systems; and, finally, those of ¤bounded treewidth. For the class of bipartite graphs, it is shown that determining the acceptability status of a specific argument can be accomplished in polynomialtime under both credulous and sceptical semantics. In addition we establish the existence of polynomial time methods for systems having bounded treewidth when deciding the following: whether a given (set of) arguments is credulously accepted; if the system has a nonempty preferred extension; has a stable extension; is coherent;
Efficient parallel algorithms for chordal graphs
"... We give the first efficient parallel algorithms for recognizing chordal graphs, finding a maximum clique and a maximum independent set in a chordal graph, finding an optimal coloring of a chordal graph, finding a breadthfirst search tree and a depthfirst search tree of a chordal graph, recognizing ..."
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Cited by 26 (0 self)
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We give the first efficient parallel algorithms for recognizing chordal graphs, finding a maximum clique and a maximum independent set in a chordal graph, finding an optimal coloring of a chordal graph, finding a breadthfirst search tree and a depthfirst search tree of a chordal graph, recognizing interval graphs, and testing interval graphs for isomorphism. The key to our results is an efficient parallel algorithm for finding a perfect elimination ordering.
Subgraph Isomorphism in Polynomial Time
, 1995
"... In this paper, we propose a new approach to the problem of subgraph isomorphism detection. The new method is designed for systems which differentiate between graphs that are a priori known, socalled model graphs, and unknown graphs, socalled input graphs. The problem to be solved is to find a subg ..."
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Cited by 24 (1 self)
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In this paper, we propose a new approach to the problem of subgraph isomorphism detection. The new method is designed for systems which differentiate between graphs that are a priori known, socalled model graphs, and unknown graphs, socalled input graphs. The problem to be solved is to find a subgraph isomorphism from an input graph, which is given online, to any of the model graphs. The new method is based on an intensive preprocessing step in which the model graphs are used to create a decision tree. At run time, the input graph is then classified by the decision tree and all model graphs for which there exists a subgraph isomorphism from the input graph are detected. If we neglect the time needed for preprocessing, the computational complexity of the new subgraph isomorphism algorithm is only quadratic in the number of input graph vertices. Furthermore, it is independent of the number of model graphs and the number of edges in any of the graphs. However, the decision tree that i...