Morgan-Claypool Book

Individual and Collective Graph Mining: Principles, Algorithms and Applications

Authors: Danai Koutra, Christos Faloutsos

Link: https://www.morganclaypool.com/doi/10.2200/S00796ED1V01Y201708DMK014

Keywords: data mining, graph mining and exploration, graph similarity, graph matching, network alignment, graph summarization, pattern mining, outlier detection, anomaly detection, scalability, fast algorithms, visualization, social networks, brain graphs, connectomes

Citation (bibtex):

@book{KoutraF17,
  author    = {Danai Koutra and
               Christos Faloutsos},
  title     = {Individual and Collective Graph Mining: Principles, Algorithms and Applications},
  publisher = {Synthesis Lectures on Data Mining and Knowledge Discovery, Morgan & Claypool}, 
  year      = {2017},
  pages     = {206}
  }

Chapter 2: Summarization of Static Graphs

VoG code (Matlab / Python)

Slides

Chapter 3: Inference in a Graph

Two Classes

FaBP code (Matlab)

Slides

Multiple Classes

mFaBP code (Python)

mFaBP code (SQL)

More detailed description & derivations

Full paper with all the proofs

Slides

Video

Chapter 4: Summarization of Dynamic Graphs

TimeCrunch code (Matlab / Python)

Slides

Chapter 5: Graph Similarity

DeltaCon code (Matlab)

DeltaCon code (R)

Slides

Tutorial slides at SDM'14 & ICDM'14

Chapter 6: Graph Alignment

Slides

Tutorial slides at SDM'14 & ICDM'14