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» On the Vulnerability of Large Graphs
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ICDCN
2011
Springer
13 years 1 months ago
A High-Level Framework for Distributed Processing of Large-Scale Graphs
Distributed processing of real-world graphs is challenging due to their size and the inherent irregular structure of graph computations. We present HIPG, a distributed framework th...
Elzbieta Krepska, Thilo Kielmann, Wan Fokkink, Hen...
PVLDB
2010
122views more  PVLDB 2010»
13 years 8 months ago
On Graph Query Optimization in Large Networks
The dramatic proliferation of sophisticated networks has resulted in a growing need for supporting effective querying and mining methods over such large-scale graph-structured da...
Peixiang Zhao, Jiawei Han
KDD
2004
ACM
114views Data Mining» more  KDD 2004»
14 years 10 months ago
Scalable mining of large disk-based graph databases
Mining frequent structural patterns from graph databases is an interesting problem with broad applications. Most of the previous studies focus on pruning unfruitful search subspac...
Chen Wang, Wei Wang 0009, Jian Pei, Yongtai Zhu, B...
SDM
2009
SIAM
138views Data Mining» more  SDM 2009»
14 years 6 months ago
ShatterPlots: Fast Tools for Mining Large Graphs.
Graphs appear in several settings, like social networks, recommendation systems, computer communication networks, gene/protein biological networks, among others. A deep, recurring...
Ana Paula Appel, Andrew Tomkins, Christos Faloutso...
DEXAW
2009
IEEE
131views Database» more  DEXAW 2009»
14 years 4 months ago
Clustering of Short Strings in Large Databases
—A novel method CLOSS intended for textual databases is proposed. It successfully identifies misspelled string clusters, even if the cluster border is not prominent. The method ...
Michail Kazimianec, Arturas Mazeika