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» The diameter of random massive graphs
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KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 6 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
PVLDB
2010
127views more  PVLDB 2010»
15 years 14 days ago
Mining Significant Semantic Locations From GPS Data
With the increasing deployment and use of GPS-enabled devices, massive amounts of GPS data are becoming available. We propose a general framework for the mining of semantically me...
Xin Cao, Gao Cong, Christian S. Jensen
INFOCOM
2008
IEEE
16 years 3 days ago
Swarming on Optimized Graphs for n-Way Broadcast
—In an n-way broadcast application each one of n overlay nodes wants to push its own distinct large data file to all other n-1 destinations as well as download their respective ...
Georgios Smaragdakis, Azer Bestavros, Nikolaos Lao...
MST
2010
187views more  MST 2010»
15 years 14 days ago
Distributed Approximation of Capacitated Dominating Sets
We study local, distributed algorithms for the capacitated minimum dominating set (CapMDS) problem, which arises in various distributed network applications. Given a network graph...
Fabian Kuhn, Thomas Moscibroda
SPAA
2004
ACM
15 years 11 months ago
Fighting against two adversaries: page migration in dynamic networks
Page migration is one of the fundamental subproblems in the framework of data management in networks. It occurs in a distributed network of processors sharing one indivisible memo...
Marcin Bienkowski, Miroslaw Korzeniowski, Friedhel...