"…individuals with no background analyzing graph data can learn how to represent the data as graphs, extract patterns or concepts from the data, and see how researchers apply the methodologies to real datasets." (Computing Reviews.com
, March 23, 2007)
From the Back Cover
Discover the latest data mining techniques for analyzing graphdata
This text takes a focused and comprehensive look at an area ofdata mining that is quickly rising to the forefront of the field:mining data that is represented as a graph. Each chapter is writtenby a leading researcher in the field; collectively, the chaptersrepresent the latest findings and applications in both theory andpractice, including solutions to many of the algorithmic challengesthat arise in mining graph data. Following the authors'step-by-step guidance, even readers with minimal background inanalyzing graph data will be able to represent data as graphs,extract patterns and concepts from the data, and apply themethodologies presented in the text to real datasets.
Mining Graph Data is divided into three parts:
- Part I, Graphs, offers an introduction to basic graphterminology and techniques.
- Part II, Mining Techniques, features a detailed examination ofcomputational techniques for extracting patterns from graph data.These techniques are the state of the art in frequent substructuremining, link analysis, graph kernels, and graph grammars.
- Part III, Applications, describes the application of datamining techniques to four graph-based application domains: chemicalgraphs, bioinformatics data, Web graphs, and social networks.
Practical case studies are included in many of the chapters. Anaccompanying Web site features source code and datasets, offeringreaders the opportunity to experiment with the techniques presentedin the book as well as test their own ideas on graph data. The Website also includes the results of many of the techniques presentedin the text.
This landmark work is intended for students and researchers incomputer science, information systems, and data mining who want tolearn how to analyze and extract useful patterns and concepts fromgraph data.