|
|
|
|
| LEADER |
04178nmm a2200445 u 4500 |
| 001 |
EB001936127 |
| 003 |
EBX01000000000000001099029 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
210123 ||| eng |
| 020 |
|
|
|a 0137047800
|
| 020 |
|
|
|a 0137047835
|
| 020 |
|
|
|a 9780137047833
|
| 050 |
|
4 |
|a QA76.9.N38
|
| 100 |
1 |
|
|a Bikel, Daniel M.
|
| 245 |
0 |
0 |
|a Multilingual natural language processing applications
|b from theory to practice
|c edited by Daniel M. Bikel, Imed Zitouni
|
| 260 |
|
|
|a Upper Saddle River, NJ
|b IBM Press
|c 2012
|
| 300 |
|
|
|a xxxix, 588 pages
|b illustrations
|
| 505 |
0 |
|
|a Includes bibliographical references and index
|
| 505 |
0 |
|
|a Part I: In Theory -- 1. Finding the Structure of Words -- 2. Finding the Structure of Documents -- 3. Syntax -- 4. Semantic Parsing -- 5. Language Modeling -- 6. Recognizing Textual Entailment -- 7. Multilingual Sentiment and Subjectivity Analysis -- Part II: In Practice -- 8. Entity Detection and Tracking -- 9. Relations and Events -- 10. Machine Translation -- 11. Multilingual Information Retrieval -- 12. Multilingual Automatic Summarization -- 13. Question Answering -- 14. Distillation -- 15. Spoken Dialog Systems -- 16. Combining Natural Language Processing Engines
|
| 653 |
|
|
|a Natural Language Processing
|
| 653 |
|
|
|a Core Programming
|
| 653 |
|
|
|a Computer Science / hilcc
|
| 653 |
|
|
|a Traitement automatique des langues naturelles
|
| 653 |
|
|
|a Engineering & Applied Sciences / hilcc
|
| 653 |
|
|
|a Natural language processing (Computer science) / fast
|
| 653 |
|
|
|a Natural language processing (Computer science) / http://id.loc.gov/authorities/subjects/sh88002425
|
| 700 |
1 |
|
|a Zitouni, Imed
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b OREILLY
|a O'Reilly
|
| 776 |
|
|
|z 9780137151448
|
| 776 |
|
|
|z 0137151446
|
| 856 |
4 |
0 |
|u https://learning.oreilly.com/library/view/~/9780137047833/?ar
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 006.3/5
|
| 082 |
0 |
|
|a 500
|
| 082 |
0 |
|
|a 620
|
| 520 |
|
|
|a Multilingual Natural Language Processing Applications is the first comprehensive single-source guide to building robust and accurate multilingual NLP systems. Edited by two leading experts, it integrates cutting-edge advances with practical solutions drawn from extensive field experience. Part I introduces the core concepts and theoretical foundations of modern multilingual natural language processing, presenting today's best practices for understanding word and document structure, analyzing syntax, modeling language, recognizing entailment, and detecting redundancy. Part II thoroughly addresses the practical considerations associated with building real-world applications, including information extraction, machine translation, information retrieval/search, summarization, question answering, distillation, processing pipelines, and more.
|
| 520 |
|
|
|a Coverage includes Core NLP problems, and today's best algorithms for attacking them Processing the diverse morphologies present in the world's languages Uncovering syntactical structure, parsing semantics, using semantic role labeling, and scoring grammaticality Recognizing inferences, subjectivity, and opinion polarity Managing key algorithmic and design tradeoffs in real-world applications Extracting information via mention detection, coreference resolution, and events Building large-scale systems for machine translation, information retrieval, and summarization Answering complex questions through distillation and other advanced techniques Creating dialog systems that leverage advances in speech recognition, synthesis, and dialog management Constructing common infrastructure for multiple multilingual text processing applications This book will be invaluable for all engineers, software developers, researchers,
|
| 520 |
|
|
|a This book contains important new contributions from leading researchers at IBM, Google, Microsoft, Thomson Reuters, BBN, CMU, University of Edinburgh, University of Washington, University of North Texas, and others.
|
| 520 |
|
|
|a and graduate students who want to process large quantities of text in multiple languages, in any environment: government, corporate, or academic
|