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Mining Graph Data - Diane J. Holder, Lawrence B. Cook
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ISBN: 9780471731900

ID: 5b3ee8d0fbdb5d6621fbcb98780efaf4

Mining Graph Data Discover the latest data mining techniques for analyzing graph data This text takes a focused and comprehensive look at an area of data mining that is quickly rising to the forefront of the field: mining data that is represented as a graph. Each chapter is written by a leading researcher in the field; collectively, the chapters represent the latest findings and applications in both theory and practice, including solutions to many of the algorithmic challenges that arise in mining graph data. Following the authors' step-by-step guidance, even readers with minimal background in analyzing graph data will 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. Mining Graph Data is divided into three parts: * Part I, Graphs, offers an introduction to basic graph terminology and techniques. * Part II, Mining Techniques, features a detailed examination of computational techniques for extracting patterns from graph data. These techniques are the state of the art in frequent substructure mining, link analysis, graph kernels, and graph grammars. * Part III, Applications, describes the application of data mining techniques to four graph-based application domains: chemical graphs, bioinformatics data, Web graphs, and social networks. Practical case studies are included in many of the chapters. An accompanying Web site features source code and datasets, offering readers the opportunity to experiment with the techniques presented in the book as well as test their own ideas on graph data. The Web site also includes the results of many of the techniques presented in the text. This landmark work is intended for students and researchers in computer science, information systems, and data mining who want to learn how to analyze and extract useful patterns and concepts from graph data. Bücher / Fremdsprachige Bücher / Englische Bücher 978-0-471-73190-0, John Wiley & Sons Inc

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Mining Graph Data - Diane J. Holder, Lawrence B. Cook
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Diane J. Holder, Lawrence B. Cook:

Mining Graph Data - neues Buch

ISBN: 9780471731900

ID: 248834b942b3ec36eb78be899eba36eb

Mining Graph Data Discover the latest data mining techniques for analyzing graph data This text takes a focused and comprehensive look at an area of data mining that is quickly rising to the forefront of the field: mining data that is represented as a graph. Each chapter is written by a leading researcher in the field; collectively, the chapters represent the latest findings and applications in both theory and practice, including solutions to many of the algorithmic challenges that arise in mining graph data. Following the authors' step-by-step guidance, even readers with minimal background in analyzing graph data will 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. Mining Graph Data is divided into three parts: * Part I, Graphs, offers an introduction to basic graph terminology and techniques. * Part II, Mining Techniques, features a detailed examination of computational techniques for extracting patterns from graph data. These techniques are the state of the art in frequent substructure mining, link analysis, graph kernels, and graph grammars. * Part III, Applications, describes the application of data mining techniques to four graph-based application domains: chemical graphs, bioinformatics data, Web graphs, and social networks. Practical case studies are included in many of the chapters. An accompanying Web site features source code and datasets, offering readers the opportunity to experiment with the techniques presented in the book as well as test their own ideas on graph data. The Web site also includes the results of many of the techniques presented in the text. This landmark work is intended for students and researchers in computer science, information systems, and data mining who want to learn how to analyze and extract useful patterns and concepts from graph data. Bücher / Fremdsprachige Bücher / Englische Bücher 978-0-471-73190-0, Wiley John + Sons

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Mining Graph Data - Diane J. Holder, Lawrence B. Cook
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Diane J. Holder, Lawrence B. Cook:
Mining Graph Data - neues Buch

ISBN: 9780471731900

ID: 5b3ee8d0fbdb5d6621fbcb98780efaf4

Mining Graph Data Discover the latest data mining techniques for analyzing graph data This text takes a focused and comprehensive look at an area of data mining that is quickly rising to the forefront of the field: mining data that is represented as a graph. Each chapter is written by a leading researcher in the field; collectively, the chapters represent the latest findings and applications in both theory and practice, including solutions to many of the algorithmic challenges that arise in mining graph data. Following the authors' step-by-step guidance, even readers with minimal background in analyzing graph data will 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. Mining Graph Data is divided into three parts: * Part I, Graphs, offers an introduction to basic graph terminology and techniques. * Part II, Mining Techniques, features a detailed examination of computational techniques for extracting patterns from graph data. These techniques are the state of the art in frequent substructure mining, link analysis, graph kernels, and graph grammars. * Part III, Applications, describes the application of data mining techniques to four graph-based application domains: chemical graphs, bioinformatics data, Web graphs, and social networks. Practical case studies are included in many of the chapters. An accompanying Web site features source code and datasets, offering readers the opportunity to experiment with the techniques presented in the book as well as test their own ideas on graph data. The Web site also includes the results of many of the techniques presented in the text. This landmark work is intended for students and researchers in computer science, information systems, and data mining who want to learn how to analyze and extract useful patterns and concepts from graph data. Bücher / Fremdsprachige Bücher / Englische Bücher 978-0-471-73190-0, John Wiley & Sons

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Mining Graph Data - Cook, Diane J.; Holder, Lawrence B.
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Cook, Diane J.; Holder, Lawrence B.:
Mining Graph Data - neues Buch

ISBN: 9780471731900

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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. Technology Technology eBook, Wiley

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2006, ISBN: 9780471731900

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Mining Graph Data
Autor:

Diane J. Cook

Titel:

Mining Graph Data

ISBN-Nummer:

9780471731900

Discover the latest data mining techniques for analyzing graph data This text takes a focused and comprehensive look at an area of data mining that is quickly rising to the forefront of the field: mining data that is represented as a graph. Each chapter is written by a leading researcher in the field; collectively, the chapters represent the latest findings and applications in both theory and practice, including solutions to many of the algorithmic challenges that arise in mining graph data. Following the authors' step-by-step guidance, even readers with minimal background in analyzing graph data will 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. Mining Graph Data is divided into three parts: * Part I, Graphs, offers an introduction to basic graph terminology and techniques. * Part II, Mining Techniques, features a detailed examination of computational techniques for extracting patterns from graph data. These techniques are the state of the art in frequent substructure mining, link analysis, graph kernels, and graph grammars. * Part III, Applications, describes the application of data mining techniques to four graph-based application domains: chemical graphs, bioinformatics data, Web graphs, and social networks. Practical case studies are included in many of the chapters. An accompanying Web site features source code and datasets, offering readers the opportunity to experiment with the techniques presented in the book as well as test their own ideas on graph data. The Web site also includes the results of many of the techniques presented in the text. This landmark work is intended for students and researchers in computer science, information systems, and data mining who want to learn how to analyze and extract useful patterns and concepts from graph data.

Detailangaben zum Buch - Mining Graph Data


EAN (ISBN-13): 9780471731900
ISBN (ISBN-10): 0471731900
Gebundene Ausgabe
Erscheinungsjahr: 2006
Herausgeber: John Wiley & Sons
500 Seiten
Gewicht: 0,839 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 26.06.2007 18:47:26
Buch zuletzt gefunden am 16.11.2016 19:29:12
ISBN/EAN: 9780471731900

ISBN - alternative Schreibweisen:
0-471-73190-0, 978-0-471-73190-0

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