Mining Graph Data

Mining Graph Data

Editor(s): Diane J. Cook, Lawrence B. Holder

Published Online: 10 APR 2006

Print ISBN: 9780471731900

Online ISBN: 9780470073049

DOI: 10.1002/0470073047

About this Book

This text takes a focused and comprehensive look at mining data represented as a graph, with the latest findings and applications in both theory and practice provided. Even if you have minimal background in analyzing graph data, with this book you'll be able to represent data as graphs, extract patterns and concepts from the data, and apply the methodologies presented in the text to real datasets.

There is a misprint with the link to the accompanying Web page for this book. For those readers who would like to experiment with the techniques found in this book or test their own ideas on graph data, the Web page for the book should be

Table of contents

    1. You have free access to this content
    2. Chapter 1

      Introduction (pages 1–14)

      Lawrence B. Holder and Diane J. Cook

    3. Chapter 9

      Constructing Decision Tree Based on Chunkingless Graph-Based Induction (pages 203–226)

      Kouzou Ohara, Phu Chien Nguyen, Akira Mogi, Hiroshi Motoda and Takashi Washio

    4. Chapter 11

      Kernel Methods for Graphs (pages 253–282)

      Thomas Gärtner, Tamás Horváth, Quoc V. Le, Alex J. Smola and Stefan Wrobel

    5. Chapter 16

      Dense Subgraph Extraction (pages 411–441)

      David Gibson, Ravi Kumar, Kevin S. McCurley and Andrew Tomkins

    6. Chapter 17

      Social Network Analysis (pages 443–468)

      Sherry E. Marcus, Melanie Moy and Thayne Coffman

    7. You have free access to this content