Table of Contents:
  • Graph matching : exact and error-tolerant methods and the automatic learning of edit costs / Horst Bunke, Michel Neuhaus
  • Graph visualization and data mining / Walter Didimo, Giuseppe Liotta
  • Graph patterns and the R-Mat generator / Deepayan Chakrabarti, Christos Faloutsos
  • Discovery of frequent substructures / Xifeng Yan, Jiawei Han
  • Finding topological frequent patterns from graph datasets / Michihiro Kuramochi, George Karypis
  • Unsupervised and supervised pattern learning in graph data / Diane J. Cook, Lawrence B. Holder, Nikhil Ketkar
  • Graph grammar learning / Istvan Jonyer
  • Constructing decision tree based on chunkingless graph-based induction / Kouzou Ohara, Phu Chien Nguyen, Akira Mogi, Hiroshi Motoda, Takashi Washio
  • Some links between formal concept analysis and graph mining / Michel Liquière
  • Kernel methods for graphs / Thomas Gärtner, Tamás Horváth, Quoc V. Le, Alex J. Smola, Stefan Wrobel
  • Kernels as link analysis measures / Masashi Shimbo, Takahiko Ito
  • Entity resolution in graphs / Indrajit Bhattacharya, Lise Getoor
  • Mining from chemical graphs / Takashi Okada
  • Unified approach to rooted tree mining : algorithms and applications / Mohammed Zaki
  • Dense subgraph extraction / David Gibson, Ravi Kumar, Kevin S. McCurley, Andrew Tomkins
  • Social network analysis / Sherry E. Marcus, Melanie Moy, Thayne Coffman.