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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Automatic Identification of Argument Elements Among Text Data of Parliamentary Debates | Automatic Identification Of Argument Elements Among Text Data of Parliamentary Debates | Vaibhav Desai (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786204206356 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Lingua: Inglese
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -Unstructured data quantum has been increased drastically in recent times. Many of the recent trends and developments in ICT has increased the unstructured data drastically, which is being increased day by day. This is resulting in the extreme difficulty in analyzing the data manually. Such a huge amount of unstructured data has been due to different reasons like increase of popularity of internet, digital content related to various domains like social media, blogs and others. Argumentation mining is one of the research area which deals with such huge quantum of unstructured data. It covers mainly the areas of 1. Information Retrieval 2. Natural Language Processing 3. Argumentation Theory. It focuses on the identification and analysis of arguments in unstructured text data. The accuracy of the result is done using various parameters like precision, recall and F-measure. The researchers have worked on a specific domain of parliamentary debates. The researchers have tried to match the results with the similar research done in other domains like legal, social media blogs and others.Books on Demand GmbH, Überseering 33, 22297 Hamburg 156 pp. Englisch.
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Da: Books Puddle, New York, NY, U.S.A.
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Da: Books Puddle, New York, NY, U.S.A.
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2025
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Unstructured data quantum has been increased drastically in recent times. Many of the recent trends and developments in ICT has increased the unstructured data drastically, which is being increased day by day. This is resulting in the extreme difficulty in analyzing the data manually. Such a huge amount of unstructured data has been due to different reasons like increase of popularity of internet, digital content related to various domains like social media, blogs and others. Argumentation mining is one of the research area which deals with such huge quantum of unstructured data. It covers mainly the areas of 1. Information Retrieval 2. Natural Language Processing 3. Argumentation Theory. It focuses on the identification and analysis of arguments in unstructured text data. The accuracy of the result is done using various parameters like precision, recall and F-measure. The researchers have worked on a specific domain of parliamentary debates. The researchers have tried to match the results with the similar research done in other domains like legal, social media blogs and others. 156 pp. Englisch.
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Desai VaibhavDr. Vaibhav Desai is working as HoD (BCA) at SDJ International College, Surat (India). He has18 years in IT Industry + 8 years in academics experience.Dr Vishal Dahiya is HoD (Computer Science Dept) at Indus University (.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204206354 ISBN 13: 9786204206356
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Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 69,73
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Unstructured data quantum has been increased drastically in recent times. Many of the recent trends and developments in ICT has increased the unstructured data drastically, which is being increased day by day. This is resulting in the extreme difficulty in analyzing the data manually. Such a huge amount of unstructured data has been due to different reasons like increase of popularity of internet, digital content related to various domains like social media, blogs and others. Argumentation mining is one of the research area which deals with such huge quantum of unstructured data. It covers mainly the areas of 1. Information Retrieval 2. Natural Language Processing 3. Argumentation Theory. It focuses on the identification and analysis of arguments in unstructured text data. The accuracy of the result is done using various parameters like precision, recall and F-measure. The researchers have worked on a specific domain of parliamentary debates. The researchers have tried to match the results with the similar research done in other domains like legal, social media blogs and others.