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» Significance-Driven Graph Clustering
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117
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ISI
2007
Springer
15 years 10 months ago
Detecting Anomalies in Graphs
Graph data represents relationships, connections, or affinities. Innocent relationships produce repeated, and so common, substructures in graph data. We present techniques for dis...
David B. Skillicorn
DATE
2009
IEEE
89views Hardware» more  DATE 2009»
15 years 11 months ago
Robust non-preemptive hard real-time scheduling for clustered multicore platforms
—Scheduling task graphs under hard (end-to-end) timing constraints is an extensively studied NP-hard problem of critical importance for predictable software mapping on Multiproce...
Michele Lombardi, Michela Milano, Luca Benini
113
Voted
APPML
2002
58views more  APPML 2002»
15 years 4 months ago
Layered clusters of tightness set functions
A method for structural clustering is proposed involving data on subset-to-entity linkages that can be calculated with structural data such as graphs or sequences or images. The m...
Boris Mirkin, Ilya B. Muchnik
STOC
2010
ACM
295views Algorithms» more  STOC 2010»
15 years 9 months ago
Approximation Schemes for Steiner Forest on Planar Graphs and Graphs of Bounded Treewidth
We give the first polynomial-time approximation scheme (PTAS) for the Steiner forest problem on planar graphs and, more generally, on graphs of bounded genus. As a first step, w...
MohammadHossein Bateni, MohammadTaghi Hajiaghayi a...
132
Voted
INFOVIS
2000
IEEE
15 years 8 months ago
Density Functions for Visual Attributes and Effective Partitioning in Graph Visualization
Two tasks in Graph Visualization require partitioning: the assignment of visual attributes and divisive clustering. Often, we would like to assign a color or other visual attribut...
Ivan Herman, M. Scott Marshall, Guy Melanço...