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» On the Vulnerability of Large Graphs
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KDD
2006
ACM
160views Data Mining» more  KDD 2006»
16 years 5 days ago
Coherent closed quasi-clique discovery from large dense graph databases
Frequent coherent subgraphscan provide valuable knowledgeabout the underlying internal structure of a graph database, and mining frequently occurring coherent subgraphs from large...
Zhiping Zeng, Jianyong Wang, Lizhu Zhou, George Ka...
PVLDB
2010
151views more  PVLDB 2010»
14 years 10 months ago
Scalable Discovery of Best Clusters on Large Graphs
The identification of clusters, well-connected components in a graph, is useful in many applications from biological function prediction to social community detection. However, ļ...
Kathy Macropol, Ambuj K. Singh
GC
2008
Springer
14 years 12 months ago
Domination in Graphs of Minimum Degree at least Two and Large Girth
We prove that for graphs of order n, minimum degree 2 and girth g 5 the domination number satisfies 1 3 + 2 3g n. As a corollary this implies that for cubic graphs of order n ...
Christian Löwenstein, Dieter Rautenbach
SIGMOD
2008
ACM
111views Database» more  SIGMOD 2008»
15 years 12 months ago
Efficiently answering reachability queries on very large directed graphs
Ruoming Jin, Yang Xiang, Ning Ruan, Haixun Wang
ICDM
2007
IEEE
118views Data Mining» more  ICDM 2007»
15 years 6 months ago
Subgraph Support in a Single Large Graph
—Defining the support (or frequency) of a subgraph is trivial when a database of graphs is given: it is simply the number of graphs in the database that contain the subgraph. Ho...
Mathias Fiedler, Christian Borgelt