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SIGMETRICS
2012
ACM
253views Hardware» more  SIGMETRICS 2012»
12 years 1 months ago
Characterizing continuous time random walks on time varying graphs
In this paper we study the behavior of a continuous time random walk (CTRW) on a stationary and ergodic time varying dynamic graph. We establish conditions under which the CTRW is...
Daniel R. Figueiredo, Philippe Nain, Bruno F. Ribe...
CORR
2011
Springer
205views Education» more  CORR 2011»
13 years 6 months ago
Random Walk on Directed Dynamic Graphs
Dynamic graphs have emerged as an appropriate model to capture the changing nature of many modern networks, such as peer-to-peer overlays and mobile ad hoc networks. Most of the re...
Oksana Denysyuk, Luis Rodrigues
ASUNAM
2010
IEEE
14 years 29 days ago
Tracking the Evolution of Communities in Dynamic Social Networks
Real-world social networks from a variety of domains can naturally be modelled as dynamic graphs. However, approaches to detecting communities have largely focused on identifying ...
Derek Greene, Dónal Doyle, Padraig Cunningh...
GD
1995
Springer
14 years 3 months ago
Incremental Layout in DynaDAG
Abstract. Generating incrementally stable layouts is important for visualizing dynamic graphs in many applications. This paper describes DynaDAG, a new heuristic for incremental la...
Stephen C. North
ICDM
2006
IEEE
149views Data Mining» more  ICDM 2006»
14 years 5 months ago
Pattern Mining in Frequent Dynamic Subgraphs
Graph-structured data is becoming increasingly abundant in many application domains. Graph mining aims at finding interesting patterns within this data that represent novel knowl...
Karsten M. Borgwardt, Hans-Peter Kriegel, Peter Wa...
WADS
2009
Springer
256views Algorithms» more  WADS 2009»
14 years 6 months ago
Dynamic Graph Clustering Using Minimum-Cut Trees
Abstract. Algorithms or target functions for graph clustering rarely admit quality guarantees or optimal results in general. Based on properties of minimum-cut trees, a clustering ...
Robert Görke, Tanja Hartmann, Dorothea Wagner
CHI
2010
ACM
14 years 6 months ago
Graphemes: self-organizing shape-based clustered structures for network visualisations
Network visualisations use clustering approaches to simplify the presentation of complex graph structures. We present a novel application of clustering algorithms, which controls ...
Ross Shannon, Aaron J. Quigley, Paddy Nixon