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Graph-theoretic techniques for web content mining / Adam Schenker ... [et al.].
- Format:
- Book
- Series:
- Series in machine perception and artificial intelligence ; v. 62.
- Series in machine perception and artificial intelligence ; v. 62
- Language:
- English
- Subjects (All):
- Data mining.
- Graph theory--Data processing.
- Graph theory.
- Algorithms.
- Multidimensional scaling.
- Physical Description:
- 1 online resource (249 p.)
- Edition:
- 1st ed.
- Place of Publication:
- [Hackensack], N.J. ; London : World Scientific, 2005.
- Language Note:
- English
- 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.
- 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
- Notes:
- Description based upon print version of record.
- Includes bibliographical references and index.
- ISBN:
- 9786611372576
- 9781281372574
- 1281372579
- 9789812569455
- 9812569456
- OCLC:
- 475976217
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