natural language processing software (9 Ergebnisse)

Tankobon Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.01.

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Empirical - data-driven, neural network-based, probabilistic, and statistical - methods seem to be the modern trend. Recently, OpenAI's ChatGPT, Google's Bard and Microsoft's Sydney chatbots have been garnering a lot of attention for their detailed answers across many knowledge domains. In consequence, most AI researchers are no longer interested in trying to understand what common intelligence is or how intelligent agents construct scenarios to solve various problems. Instead, they now develop systems that extract solutions from massive databases used as cheat sheets. In the same manner, Natural Language Processing (NLP) software that uses training corpora associated with empirical methods are trendy, as most researchers in NLP today use large training corpora, always to the detriment of the development of formalized dictionaries and grammars.Not questioning the intrinsic value of many software applications based on empirical methods, this volume aims at rehabilitating the linguistic approach to NLP. In an introduction, the editor uncovers several limitations and flaws of using training corpora to develop NLP applications, even the simplest ones, such as automatic taggers.The first part of the volume is dedicated to showing how carefully handcrafted linguistic resources could be successfully used to enhance current NLP software applications. The second part presents two representative cases where data-driven approaches cannot be implemented simply because there is not enough data available for low-resource languages. The third part addresses the problem of how to treat multiword units in NLP software, which is arguably the weakest point of NLP applications today but has a simple and elegant linguistic solution.It is the editor's belief that readers interested in Natural Language Processing will appreciate the importance of this volume, both for its questioning of the training corpus-based approaches and for the intrinsic value of the linguistic formalization and the underlying methodology presented.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Empirical - data-driven, neural network-based, probabilistic, and statistical - methods seem to be the modern trend. Recently, OpenAI's ChatGPT, Google's Bard and Microsoft's Sydney chatbots have been garnering a lot of attention for their detailed answers across many knowledge domains. In consequence, most AI researchers are no longer interested in trying to understand what common intelligence is or how intelligent agents construct scenarios to solve various problems. Instead, they now develop systems that extract solutions from massive databases used as cheat sheets. In the same manner, Natural Language Processing (NLP) software that uses training corpora associated with empirical methods are trendy, as most researchers in NLP today use large training corpora, always to the detriment of the development of formalized dictionaries and grammars.Not questioning the intrinsic value of many software applications based on empirical methods, this volume aims at rehabilitating the linguistic approach to NLP. In an introduction, the editor uncovers several limitations and flaws of using training corpora to develop NLP applications, even the simplest ones, such as automatic taggers.The first part of the volume is dedicated to showing how carefully handcrafted linguistic resources could be successfully used to enhance current NLP software applications. The second part presents two representative cases where data-driven approaches cannot be implemented simply because there is not enough data available for low-resource languages. The third part addresses the problem of how to treat multiword units in NLP software, which is arguably the weakest point of NLP applications today but has a simple and elegant linguistic solution.It is the editor's belief that readers interested in Natural Language Processing will appreciate the importance of this volume, both for its questioning of the training corpus-based approaches and for the intrinsic value of the linguistic formalization and the underlying methodology presented.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Buch. Zustand: Neu. Neuware - Discover how Natural Language Processing for Software Engineering can transform your understanding of agile development, equipping you with essential tools and insights to enhance software quality and responsiveness in today's rapidly changing technological landscape.

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Hardcover. Zustand: Brand New. 239 pages. 9.25x6.10x9.21 inches. In Stock.

Hardcover. Zustand: Brand New. 544 pages. 9.29x6.22x1.42 inches. In Stock.