Book Cover
E-book

Title Graph-theoretic techniques for web content mining / Adam Schenker [and others]
Published Singapore ; Hackensack, N.J. : World Scientific, [2005]
©2005
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Description 1 online resource (249 pages)
Series Series in machine perception and artificial intelligence ; v. 62
Series in machine perception and artificial intelligence ; v. 62
Contents Preface; Contents; Chapter 1 Introduction to Web Mining; Chapter 2 Graph Similarity Techniques; Chapter 3 Graph Models for Web Documents; Chapter 4 Graph-Based Clustering; Chapter 5 Graph-Based Classification; Chapter 6 The Graph Hierarchy Construction Algorithm for Web Search Clustering; Chapter 7 Conclusions and Future Work; Appendix A Graph Examples; Appendix B List of Stop Words; Bibliography; Index
Summary This book describes exciting new opportunities for utilizing robust graph representations of data with common machine learning algorithms. Graphs can model additional information which is often not present in commonly used data representations, such as vectors
Notes Title from title screen
Bibliography Includes bibliographical references and index
Subject Algorithms.
Data mining.
Graph theory -- Data processing.
Multidimensional scaling.
Form Electronic book
Author Schenker, Adam.
ISBN 1281372579
9781281372574
9789812563392
9789812569455 (electronic bk.)
9812563393
9812569456 (electronic bk.)
Other Titles ITPro