The Text Mining Handbook
Advanced Approaches in Analyzing Unstructured Data

Covers text mining and link detection algorithms, pre-processing techniques, knowledge representation, visualization and applications.

Ronen Feldman (Author), James Sanger (Author)

9780521836579, Cambridge University Press

Hardback, published 11 December 2006

424 pages
25.4 x 17.8 x 2.4 cm, 0.95 kg

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

Text mining is a new and exciting area of computer science research that tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. Similarly, link detection – a rapidly evolving approach to the analysis of text that shares and builds upon many of the key elements of text mining – also provides new tools for people to better leverage their burgeoning textual data resources. The Text Mining Handbook 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. Finally, the book explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities.

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.

Subject Areas: Pattern recognition [UYQP], Expert systems / knowledge-based systems [UYQE], Data mining [UNF]