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» On the Vulnerability of Large Graphs
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APVIS
2011
12 years 9 months ago
Multilevel agglomerative edge bundling for visualizing large graphs
Graphs are often used to encapsulate relationships between objects. Node-link diagrams, commonly used to visualize graphs, suffer from visual clutter on large graphs. Edge bundlin...
Emden R. Gansner, Yifan Hu, Stephen C. North, Carl...
KDD
2008
ACM
165views Data Mining» more  KDD 2008»
14 years 10 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...
CORR
2010
Springer
142views Education» more  CORR 2010»
13 years 8 months ago
HyperANF: Approximating the Neighbourhood Function of Very Large Graphs on a Budget
The neighbourhood function NG(t) of a graph G gives, for each t ∈ N, the number of pairs of nodes x, y such that y is reachable from x in less that t hops. The neighbourhood fun...
Paolo Boldi, Marco Rosa, Sebastiano Vigna
VLDB
2005
ACM
177views Database» more  VLDB 2005»
14 years 3 months ago
Discovering Large Dense Subgraphs in Massive Graphs
We present a new algorithm for finding large, dense subgraphs in massive graphs. Our algorithm is based on a recursive application of fingerprinting via shingles, and is extreme...
David Gibson, Ravi Kumar, Andrew Tomkins
PUK
2000
13 years 11 months ago
An Accessibility graph learning approach for task planning in large domains
Abstract. In the stream of research that aims to speed up practical planners, we propose a new approach to task planning based on Probabilistic Roadmap Methods (PRM). Our contribut...
Emmanuel Guere, Rachid Alami