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SIGMOD
2008
ACM
191views Database» more  SIGMOD 2008»
10 years 2 months ago
Efficient aggregation for graph summarization
Graphs are widely used to model real world objects and their relationships, and large graph datasets are common in many application domains. To understand the underlying character...
Yuanyuan Tian, Richard A. Hankins, Jignesh M. Pate...
KDD
2002
ACM
182views Data Mining» more  KDD 2002»
10 years 2 months ago
ANF: a fast and scalable tool for data mining in massive graphs
Graphs are an increasingly important data source, with such important graphs as the Internet and the Web. Other familiar graphs include CAD circuits, phone records, gene sequences...
Christopher R. Palmer, Phillip B. Gibbons, Christo...
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
9 years 3 months ago
Patterns of Cascading Behavior in Large Blog Graphs
How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we ...
Jure Leskovec, Mary McGlohon, Christos Faloutsos, ...
CVPR
2008
IEEE
10 years 4 months ago
Unsupervised modeling of object categories using link analysis techniques
We propose an approach for learning visual models of object categories in an unsupervised manner in which we first build a large-scale complex network which captures the interacti...
Gunhee Kim, Christos Faloutsos, Martial Hebert
PKDD
2010
Springer
155views Data Mining» more  PKDD 2010»
9 years 25 days ago
Latent Structure Pattern Mining
Pattern mining methods for graph data have largely been restricted to ground features, such as frequent or correlated subgraphs. Kazius et al. have demonstrated the use of elaborat...
Andreas Maunz, Christoph Helma, Tobias Cramer, Ste...
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