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» Frequent Sub-graph Mining on Edge Weighted Graphs
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ICDM
2006
IEEE
149views Data Mining» more  ICDM 2006»
13 years 11 months ago
Pattern Mining in Frequent Dynamic Subgraphs
Graph-structured data is becoming increasingly abundant in many application domains. Graph mining aims at finding interesting patterns within this data that represent novel knowl...
Karsten M. Borgwardt, Hans-Peter Kriegel, Peter Wa...
ICDM
2007
IEEE
197views Data Mining» more  ICDM 2007»
13 years 11 months ago
Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks
Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of...
Ruoming Jin, Scott McCallen, Eivind Almaas
SDM
2010
SIAM
213views Data Mining» more  SDM 2010»
13 years 7 months ago
Spectral Analysis of Signed Graphs for Clustering, Prediction and Visualization
We study the application of spectral clustering, prediction and visualization methods to graphs with negatively weighted edges. We show that several characteristic matrices of gra...
Jérôme Kunegis, Stephan Schmidt, Andr...
KDD
2008
ACM
192views Data Mining» more  KDD 2008»
14 years 5 months ago
Partial least squares regression for graph mining
Attributed graphs are increasingly more common in many application domains such as chemistry, biology and text processing. A central issue in graph mining is how to collect inform...
Hiroto Saigo, Koji Tsuda, Nicole Krämer
SDM
2004
SIAM
194views Data Mining» more  SDM 2004»
13 years 6 months ago
Finding Frequent Patterns in a Large Sparse Graph
Graph-based modeling has emerged as a powerful abstraction capable of capturing in a single and unified framework many of the relational, spatial, topological, and other characteri...
Michihiro Kuramochi, George Karypis