Description

Book Synopsis
Presents a comprehensive discussion of the state-of-the-art in text mining and link detection. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, the book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches, ending with real-world, mission-critical applications.

Trade Review
' … buy the book. This book is definitely worth having in your book shelf as a handy reference.' IAPR Newsletter

Table of Contents
1. Introduction to text mining; 2. Core text mining operations; 3. Text mining preprocessing techniques; 4. Categorization; 5. Clustering; 6. Information extraction; 7. Probabilistic models for Information extraction; 8. Preprocessing applications using probabilistic and hybrid approaches; 9. Presentation-layer considerations for browsing and query refinement; 10. Visualization approaches; 11. Link analysis; 12. Text mining applications; Appendix; Bibliography.

The Text Mining Handbook

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£74.99

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Order before 4pm today for delivery by Thu 18 Dec 2025.

A Hardback by Ronen Feldman, James Sanger

15 in stock


    View other formats and editions of The Text Mining Handbook by Ronen Feldman

    Publisher: Cambridge University Press
    Publication Date: 12/11/2006 12:00:00 AM
    ISBN13: 9780521836579, 978-0521836579
    ISBN10: 0521836573

    Description

    Book Synopsis
    Presents a comprehensive discussion of the state-of-the-art in text mining and link detection. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, the book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches, ending with real-world, mission-critical applications.

    Trade Review
    ' … buy the book. This book is definitely worth having in your book shelf as a handy reference.' IAPR Newsletter

    Table of Contents
    1. Introduction to text mining; 2. Core text mining operations; 3. Text mining preprocessing techniques; 4. Categorization; 5. Clustering; 6. Information extraction; 7. Probabilistic models for Information extraction; 8. Preprocessing applications using probabilistic and hybrid approaches; 9. Presentation-layer considerations for browsing and query refinement; 10. Visualization approaches; 11. Link analysis; 12. Text mining applications; Appendix; Bibliography.

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