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 http: //www.eecs.wsu.edu/MGD.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
DIANE J. COOK, PhD, is the Huie-Rogers Chair Professor in the School of Electrical Engineering and Computer Science at Washington State University. Her extensive research in artificial intelligence and data mining has been supported by grants from the National Science Foundation, NASA, DARPA, and Texas Instruments. Dr. Cook is the coauthor of Smart Environments: Technology, Protocols, and Applications (Wiley).
LAWRENCE B. HOLDER, PhD, is Professor in the School of Electrical Engineering and Computer Science at Washington State University, where he teaches and conducts research in artificial intelligence, machine learning, data mining, graph theory, parallel and distributed processing, and cognitive architectures.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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