Sciweavers

CIKM
2010
Springer
13 years 6 months ago
Mining networks with shared items
Recent advances in data processing have enabled the generation of large and complex graphs. Many researchers have developed techniques to investigate informative structures within...
Jun Sese, Mio Seki, Mutsumi Fukuzaki
TVCG
2008
145views more  TVCG 2008»
13 years 11 months ago
Geometry-Based Edge Clustering for Graph Visualization
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, ...
BMCBI
2010
183views more  BMCBI 2010»
13 years 11 months ago
SING: Subgraph search In Non-homogeneous Graphs
Background: Finding the subgraphs of a graph database that are isomorphic to a given query graph has practical applications in several fields, from cheminformatics to image unders...
Raffaele Di Natale, Alfredo Ferro, Rosalba Giugno,...
APVIS
2001
14 years 25 days ago
Building Virtual Worlds with the Big-Bang Model
Visualisations implemented as virtual worlds can allow users to comprehend large graphs more effectively. Good 3D layout algorithms are an important element. Angle has been develo...
Neville Churcher, Alan Creek
GD
2006
Springer
14 years 3 months ago
Eigensolver Methods for Progressive Multidimensional Scaling of Large Data
We present a novel sampling-based approximation technique for classical multidimensional scaling that yields an extremely fast layout algorithm suitable even for very large graphs....
Ulrik Brandes, Christian Pich
ICCTA
2007
IEEE
14 years 3 months ago
What Graphs can be Efficiently Represented by BDDs?
We have carried out experimental research into implicit representation of large graphs using reduced ordered binary decision diagrams (OBDDs). We experimentally show that for grap...
Changxing Dong, Paul Molitor
IWPC
2000
IEEE
14 years 3 months ago
The Effect of Call Graph Construction Algorithms for Object-Oriented Programs on Automatic Clustering
Call graphs are commonly used as input for automatic clustering algorithms, the goal of which is to extract the high level structure of the program under study. Determining the ca...
Derek Rayside, Steve Reuss, Erik Hedges, Kostas Ko...
GD
2004
Springer
14 years 4 months ago
A Note on the Self-similarity of Some Orthogonal Drawings
Large graphs are difficult to browse and to visually explore. This note adds up evidence that some graph drawing techniques, which produce readable layouts when applied to medium-s...
Maurizio Patrignani
IV
2005
IEEE
131views Visualization» more  IV 2005»
14 years 5 months ago
A Framework for Visualising Large Graphs
Visualising large graphs faces the challenges of both data complexity and visual complexity. This paper presents a framework for visualising large graphs that reduces data complex...
Wanchun Li, Seok-Hee Hong, Peter Eades
HIPC
2007
Springer
14 years 5 months ago
Accelerating Large Graph Algorithms on the GPU Using CUDA
Abstract. Large graphs involving millions of vertices are common in many practical applications and are challenging to process. Practical-time implementations using high-end comput...
Pawan Harish, P. J. Narayanan