145 search results - page 9 / 29 » Mining closed relational graphs with connectivity constraint... |
112
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EDBT
2012
ACM
13 years 2 months ago
2012
ACM
In this paper, we study how to find maximal k-edge-connected subgraphs from a large graph. k-edge-connected subgraphs can be used to capture closely related vertices, and findin...
KDD
2003
ACM
16 years 1 days ago
2003
ACM
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
113
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DLOG
2011
14 years 3 months ago
2011
Linked Data makes one central addition to the Semantic Web principles: all entity URIs should be dereferenceable to provide an authoritative RDF representation. URIs in a linked da...
SIGMOD
2010
ACM
15 years 4 months ago
2010
ACM
Mining graph patterns in large networks is critical to a variety of applications such as malware detection and biological module discovery. However, frequent subgraphs are often i...
103
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PKDD
2010
Springer
14 years 9 months ago
2010
Springer
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...