Practical Graph Mining with R

Nagiza F. Samatova is an associate professor of computer science at North Carolina State University and a senior research scientist at Oak Ridge National Laboratory.

"The authors provide a tour de force introduction to the different data representations (vectors, matrices), and introduce graph structures and the questions that can be answered with them. ... The book has many strong points. There is a companion website that hosts slide presentations for almost all chapters, as well the R code needed to run the example code. The impatient reader can start going through the presentations and experimenting with the code right away. The more patient reader can read the book from cover to cover. For many reader categories, this summary of existing relevant work and approaches for data mining graph structures is a welcome addition, for which the authors deserves much praise."--Radu State, Computing Reviews

• Introduction. An Introduction to Graph Theory. An Introduction to R. An Introduction to Kernel Functions. Link Analysis. Graph-Based Proximity Measures. Frequent Subgraph Mining. Cluster Analysis. Classification. Dimensionality Reduction. Graph-Based Anomaly Detection. Performance Metrics for Graph Mining Tasks. Introduction to Parallel Graph Mining. Index.