Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications
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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,…mehr

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Produktbeschreibung
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.
Autorenporträt
Venkat N. Gudivada is a professor and chair of the Computer Science Department at East Carolina University. Prior to this, he was a professor and founding chair of the Weisberg Division of Computer Science at Marshall University. His industry tenure spans over six years as a vice president for Wall Street companies in the New York City area including Merrill Lynch (now Bank of America Merrill Lynch) and Financial Technologies International (now GoldenSource). Previous academic tenure includes work at the University of Michigan, University of Missouri, and Ohio University.

He has published over 90 peer-reviewed technical articles and rendered professional service in various roles including conference program chair, keynote speaker, program committee member, and guest editor of IEEE journals. Gudivada's research sponsors include National Science Foundation (NSF), National Aeronautics and Space Administration (NASA), U.S. Department of Energy, U.S. Department of Navy, U.S. Army Research Office, MU Foundation, and WV Division of Science and Research. His current research interests encompass Big Data Management, High Performance Computing, Information Retrieval, Image and Natural Language Processing, and Personalized Learning. Gudivada received a PhD degree in Computer Science from the University of Louisiana at Lafayette.