Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
Joshua J. Forman, Paul A. Clemons, Stuart L. Schre...
In this paper we propose a conductance electrical model to represent weighted undirected graphs that allows us to efficiently compute approximate graph isomorphism in large graph...
1 In web-related applications of image categorization, it is desirable to derive an interpretable classification rule with high accuracy. Using the bag-of-words representation and...
Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku K...
We present a new approach aimed at understanding the structure of connections in edge-bundling layouts. We combine the advantages of edge bundles with a bundle-centric simplified ...
Graphs have been widely used to model relationships among data. For large graphs, excessive edge crossings make the display visually cluttered and thus difficult to explore. In thi...
Weiwei Cui, Hong Zhou, Huamin Qu, Pak Chung Wong, ...