Practical Graph Mining with R (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
|Rating||:||4.69 (562 Votes)|
|Number of Pages||:||495 Pages|
An excellent addition to my personal library This is definitely a practical book. An excellent addition to my personal library.. Five Stars Mark Coy great book.
It covers many basic and advanced techniques for the identification of anomalous or frequently recurring patterns in a graph, the discovery of groups or clusters of nodes that share common patterns of attributes and relationships, the extraction of patterns that distinguish one category of graphs from another, and the use of those patterns to predict the category of new graphs.Hands-On Application of Graph Data MiningEach chapter in the book focuses on a graph mining task, such as link analysis, clu
Samatova is an associate professor of computer science at North Carolina State University and a senior research scientist at Oak Ridge National Laboratory.. Nagiza F
The book has many strong points. 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. 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 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 more patient reader can read the book from c