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Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications de C. R. Rao

Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications: Handbook of Statistics, cartea 38

C. R. Rao Venkat N. Gudivada
en Limba Engleză Hardback – 29 aug 2018
Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications, Volume 38, the latest release in this monograph that provides a cohesive and integrated exposition of these advances and associated applications, includes new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, Inference and Prediction Methods, Random Processes, Bayesian Methods, Machine Learning, Artificial Neural Networks for Natural Language Processing, Information Retrieval, Language Core Tasks, Language Understanding Applications, and more.
The synergistic confluence of linguistics, statistics, big data, and high-performance computing is the underlying force for the recent and dramatic advances in analyzing and understanding natural languages, hence making this series all the more important.


  • Provides a thorough treatment of open-source libraries, application frameworks and workflow systems for natural language analysis and understanding
  • Presents new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, and more
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Specificații

ISBN-13: 9780444640420
ISBN-10: 0444640428
Pagini: 537
Dimensiuni: 152 x 229 x 34 mm
Greutate: 0.89 kg
Editura: ELSEVIER SCIENCE
Seria Handbook of Statistics

Public țintă

This monograph is intended to fill the dire need for a scholarly compendium of recent research, transformational and non-traditional applications of natural language understanding. It is intended to serve as an authoritative reference and handbook for industry practitioners, educators, and students alike. The intended audience for the monograph are industry practitioners, researchers, educators, graduate and undergraduate students.
The monograph is unique and one of its kind. It unifies linguistics theory, statistical methods, machine learning algorithms, and high-performance computing, which are essential to gain insights into current approaches to natural language processing and understanding. Researchers will benefit from a cohesive and integrated body of knowledge drawn from the underlying disciplines. It will provide them an accessible and convenient resource to quickly learn the state-of-the-art. Many universities are introducing courses in natural language understanding in the backdrop of the immense popularity of IBM Watson, a question-answering system that won Jeopardy! game championship in 2011. This is in contrast with only select research-intensive universities which offered courses in this area until recently. The monograph is suitable for teaching classes at both graduate and undergraduate levels.
Several open-source datasets, libraries, application frameworks, and workflow systems are discussed. These resources are valuable for readers who want to engage in experimentation for deepening their understanding.

Cuprins

1. Linguistics: Core Concepts and Principles
2. Grammars
3. Open-Source Libraries, Application Frameworks, Workflow Systems, and Other Resources
4. Mathematical Essentials
5. Probability
6. Inference and Prediction Methods
7. Random Processes
8. Bayesian Methods
9. Machine Learning
10. Artificial Neural Networks for Natural Language Processing
11. Information Retrieval
12. Language Core Tasks 1
13. Language Core Tasks 2
14. Language Understanding Applications 1
15. Language Understanding Applications 2
16. Deep Learning for Natural Language Processing
17. Text Mining for Modeling Cyberattacks
18. World Languages and Crosslinguistics
19. Linguistic Elegance of the Languages of South India
20. Current Trends and Open Problems