Computational analysis and understanding of natural languages : principles, methods and applications Volume 38 [eBook] / edited by Venkat N. Gudivada and C.R. Rao.
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| Edition | 1st ed. |
| Publication | |
| Contents | 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. |
| Multimedia | |
| Physical Description | 1 online resource (xxi, 515 pages) : ill., digital, PDF file(s). |
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$a Computational analysis and understanding of natural languages : $b principles, methods and applications $n Volume 38 $h [eBook] / $c edited by Venkat N. Gudivada and C.R. Rao.
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$a 1st ed.
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$a Amsterdam, Netherlands : $b North Holland, is an imprint of Elsevier, $c ©2018.
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$a 1 online resource (xxi, 515 pages) : $b ill., digital, PDF file(s).
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$a Handbook of statistics ; $v Volume 38.
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$a Includes bibliographical references and index.
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$a 1. Linguistics: Core Concepts and Principles--2. Grammars--3. Open-Source Libraries, Application Frameworks, Workflow Systems, and Other Resources--4. Mathematical Essentials--5. Probability--6. Inference and Prediction Methods--7. Random Processes--8. Bayesian Methods--9. Machine Learning--10. Artificial Neural Networks for Natural Language Processing--11. Information Retrieval--12. Language Core Tasks 1--13. Language Core Tasks 2--14. Language Understanding Applications 1--15. Language Understanding Applications 2--16. Deep Learning for Natural Language Processing--17. Text Mining for Modeling Cyberattacks--18. World Languages and Crosslinguistics--19. Linguistic Elegance of the Languages of South India--20. Current Trends and Open Problems.
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$a 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.
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$a Computational linguistics.
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$a Natural language processing (Computer science)
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$a Semantics $x Data processing.
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$a Gudivada, Venkat N., $e editor.
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$a Rao, C.R., $e editor.
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$i Printed edition: $z 9780444640420
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$a Handbook of statistics ; $v Volume 38.
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$u https://www.sciencedirect.com/handbook/handbook-of-statistics/vol/38/suppl/C $y Click here to view eBook.
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| Summary | 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. |