natural language processing software (29 resultados)

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Hardcover. Condición: new. Hardcover. 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 todays rapidly changing technological landscape. Agile development enhances business responsiveness through continuous software delivery, emphasizing iterative methodologies that produce incremental, usable software. Working software is the main measure of progress, and ongoing customer collaboration is essential. Approaches like Scrum, eXtreme Programming (XP), and Crystal share these principles but differ in focus: Scrum reduces documentation, XP improves software quality and adaptability to changing requirements, and Crystal emphasizes people and interactions while retaining key artifacts. Modifying software systems designed with Object-Oriented Analysis and Design can be costly and time-consuming in rapidly changing environments requiring frequent updates. This book explores how natural language processing can enhance agile methodologies, particularly in requirements engineering. It introduces tools that help developers create, organize, and update documentation throughout the agile project process. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Taschenbuch. Condición: 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.

Buch. Condición: 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.

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Hardcover. Condición: new. Hardcover. 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 todays rapidly changing technological landscape. Agile development enhances business responsiveness through continuous software delivery, emphasizing iterative methodologies that produce incremental, usable software. Working software is the main measure of progress, and ongoing customer collaboration is essential. Approaches like Scrum, eXtreme Programming (XP), and Crystal share these principles but differ in focus: Scrum reduces documentation, XP improves software quality and adaptability to changing requirements, and Crystal emphasizes people and interactions while retaining key artifacts. Modifying software systems designed with Object-Oriented Analysis and Design can be costly and time-consuming in rapidly changing environments requiring frequent updates. This book explores how natural language processing can enhance agile methodologies, particularly in requirements engineering. It introduces tools that help developers create, organize, and update documentation throughout the agile project process. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Hardcover. Condición: new. Hardcover. 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 todays rapidly changing technological landscape. Agile development enhances business responsiveness through continuous software delivery, emphasizing iterative methodologies that produce incremental, usable software. Working software is the main measure of progress, and ongoing customer collaboration is essential. Approaches like Scrum, eXtreme Programming (XP), and Crystal share these principles but differ in focus: Scrum reduces documentation, XP improves software quality and adaptability to changing requirements, and Crystal emphasizes people and interactions while retaining key artifacts. Modifying software systems designed with Object-Oriented Analysis and Design can be costly and time-consuming in rapidly changing environments requiring frequent updates. This book explores how natural language processing can enhance agile methodologies, particularly in requirements engineering. It introduces tools that help developers create, organize, and update documentation throughout the agile project process. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Linguistic Knowledge Builder (LKB) is a free and open source grammar engineering environment for creating grammars and lexicons of natural languages. Any unification-based grammar can be implemented, but LKB is typically used for grammars with typed feature structures such as HPSG. It is implemented in Common Lisp, and constitutes one core component of the DELPH-IN collaboration.

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Taschenbuch. Condición: Neu. LKB | Free Software, Open Source, Grammar, Natural Language Processing | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786131927980 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

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Buch. Condición: Neu. Linguistic Resources for Natural Language Processing | On the Necessity of Using Linguistic Methods to Develop NLP Software | Max Silberztein | Buch | xxii | Englisch | 2024 | Palgrave Macmillan | EAN 9783031438103 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

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