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Linguistic Resources for Natural Language Processing: On the Necessity of Using Linguistic Methods to Develop NLP Software
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Linguistic Resources for Natural Language Processing : On the Necessity of Using Linguistic Methods to Develop Nlp Software
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Linguistic Resources for Natural Language Processing : On the Necessity of Using Linguistic Methods to Develop Nlp Software
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Natural Language Processing for Software Engineering
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Linguistic Resources for Natural Language Processing | On the Necessity of Using Linguistic Methods to Develop NLP Software
Language: English
Published by Springer Nature Switzerland, 2025
ISBN 10: 3031438132 ISBN 13: 9783031438134
Taschenbuch. Condition: Neu. Linguistic Resources for Natural Language Processing | On the Necessity of Using Linguistic Methods to Develop NLP Software | Max Silberztein | Taschenbuch | xxii | Englisch | 2025 | Springer Nature Switzerland | EAN 9783031438134 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Natural Language Processing for Software Engineering
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Linguistic Resources for Natural Language Processing : On the Necessity of Using Linguistic Methods to Develop NLP Software
Language: English
Published by Springer Nature Switzerland, Springer Nature Switzerland, 2024
ISBN 10: 3031438108 ISBN 13: 9783031438103
Buch. Condition: 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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Linguistic Resources for Natural Language Processing : On the Necessity of Using Linguistic Methods to Develop NLP Software
Language: English
Published by Springer Nature Switzerland, Springer Nature Switzerland, 2025
ISBN 10: 3031438132 ISBN 13: 9783031438134
Taschenbuch. Condition: 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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Natural Language Processing for Software Engineering
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Linguistic Resources for Natural Language Processing: On the Necessity of Using Linguistic Methods to Develop Nlp Software
Language: English
Published by Springer-Nature New York Inc, 2024
ISBN 10: 3031438108 ISBN 13: 9783031438103
Hardcover. Condition: Brand New. 239 pages. 9.25x6.10x9.21 inches. In Stock.
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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Hardcover. Condition: Brand New. 544 pages. 9.29x6.22x1.42 inches. In Stock.
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International EditionNATURAL LANGUAGE PROCESSING FOR SOFTWARE ENGINEERING (HB 2025)
Language: English
Published by JOHN WILEY NP (ORIGINAL), 2025
ISBN 10: 139427243X ISBN 13: 9781394272433
Condition: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! High Quality Content by WIKIPEDIA articles! LanguageWare is a natural language processing (NLP) technology developed by IBM, that allows applications to process natural language text. It comprises a set of Java libraries which provide a range of NLP functions: language identification, text segmentation/tokenization, normalization, entity and relationship extraction, and semantic analysis and disambiguation. The analysis engine uses Finite State Machine approach at multiple levels, which aids its performance characteristics, while maintaining a reasonably small footprint.
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Taschenbuch. Condition: 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. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.
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Taschenbuch. Condition: Neu. Languageware | Finite State Machine, Natural Language Processing, Eclipse (Software), Web Services, UIMA, Linguistics | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786131174070 | 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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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.
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Taschenbuch. Condition: 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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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.
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