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.

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 NP-complete. Many sub-disciplines 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 polynomial-time 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...

In this paper an improved version of a graph matching algorithm is presented, which is able to efficiently solve the graph isomorphism and graph-subgraph 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.

We describe a sensor network deployment method using autonomous flying robots. Such networks are suitable for tasks such as large-scale 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~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 hand-printed numerals confirmed the method’s high robustness level. Zndex Terms-Shape distance, graph matching, relative neighborhood graph, broken character recognition, subgraph homeomorphism. I.

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.

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 breadth-first search tree and a depth-first 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.

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, so-called model graphs, and unknown graphs, so-called input graphs. The problem to be solved is to find a subgraph isomorphism from an input graph, which is given on-line, 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...

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, co-NP, 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 graph-theoretic restrictions is considered: ¤-partite systems (¤¦¥¨ § ) in which the set of arguments may be partitioned into ¤ sets each of which is conflict-free; 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 polynomial-time 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 non-empty preferred extension; has a stable extension; is coherent;

The k-dimensional Weisfeiler-Leman algorithm, for k 1, is a natural and simple combinatorial algorithm attempting to decide whether two given graphs are isomorphic. In this paper, we show that for every surface S (orientable or non-orientable) there is a k 1 such that the k-dimensional WL-algorithm succeeds to decide isomorphism of graphs embeddable in S. To prove this, we use a close connection between the WL-algorithm and denability in certain nite variable logics that has been established by Cai, Furer, and Immerman [7]. 1. INTRODUCTION The graph isomorphism problem asks whether two given graphs are isomorphic. While complexity theoretic results indicate that the isomorphism problem is not NP-complete (if it was, the polynomial hierarchy would collapse to its second level [6; 29]), no polynomial time algorithm for the general problem is known. However, there is a number of important classes of graphs on which the isomorphism problem is known to be solvable in polynomial t...