This text covers the technologies of document retrieval, information extraction, and text categorization in a way which highlights commonalities in terms of both general principles and practical concerns. It assumes some mathematical background on the part of the reader, but the chapters typically begin with a non-mathematical account of the key issues. Current research topics are covered only to the extent that they are informing current applications; detailed coverage of longer term research and more theoretical treatments should be sought elsewhere. There are many pointers at the ends of the chapters that the reader can follow to explore the literature. However, the book does maintain a strong emphasis on evaluation in every chapter both in terms of methodology and the results of controlled experimentation.
Reihe
Auflage
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Editions-Typ
Maße
Höhe: 240 mm
Breite: 160 mm
Gewicht
ISBN-13
978-90-272-4993-7 (9789027249937)
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Schweitzer Klassifikation
1. Preface to the 2nd edition; 2. Chapter 1. Natural language processing; 3. 1.1 What is NLP?; 4. 1.2 NLP and linguistics; 5. 1.3 Linguistic tools; 6. 1.4 Plan of the book; 7. Chapter 2. Document retrieval; 8. 2.1 Information retrieval; 9. 2.2 Indexing technology; 10. 2.3 Query processing; 11. 2.4 Evaluating search engines; 12. 2.5 Attempts to enhance search performance; 13. 2.6 The future ofWeb searching; 14. Chapter 3. Information extraction; 15. 3.1 The message understanding conferences; 16. 3.2 Regular expressions; 17. 3.3 Finite automata in FASTUS; 18. 3.4 Context-free grammars; 19. 3.5 Limitations of current technology and future research; 20. 3.6 Summary of information extraction; 21. Chapter 4. Text categorization; 22. 4.1 Overview of categorization tasks; 23. 4.2 Handcrafted rule based methods; 24. 4.3 Inductive learning for text classification; 25. 4.4 Nearest neighbor algorithms; 26. 4.5 Combining classifiers; 27. 4.6 Evaluation of text categorization systems; 28. Chapter 5. Text mining; 29. 5.1 What is text mining?; 30. 5.2 Resolving reference and coreference; 31. 5.3 Automatic summarization; 32. 5.4 Testing of automatic summarization programs; 33. 5.5 Prospects for text mining and NLP; 34. References; 35. Index
