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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 6 months 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»
15 years 4 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
15 years 5 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»
16 years 6 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»
16 years 3 days 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