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Idioma: Inglés
Publicado por Springer International Publishing, 2022
ISBN 10: 303110868X ISBN 13: 9783031108686
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 160,49
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to influence business, politics, security, planning and other social aspects. Recently, deep learning techniques have had many successful applications in the AI field. The research presented in this book emerges from the conviction that there is still much progress to be made toward exploiting deep learning in the context of social media data analytics. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis. This work could serve as a good reference for researchers, as well as a compilation of innovative ideas and solutions for practitioners interested in applying deep learning techniques to social media data analytics.
Idioma: Inglés
Publicado por Springer-Nature New York Inc, 2022
ISBN 10: 303110868X ISBN 13: 9783031108686
Librería: Revaluation Books, Exeter, Reino Unido
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Idioma: Inglés
Publicado por Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10: 303110868X ISBN 13: 9783031108686
Librería: moluna, Greven, Alemania
EUR 136,16
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to .
Idioma: Inglés
Publicado por Springer International Publishing Sep 2022, 2022
ISBN 10: 303110868X ISBN 13: 9783031108686
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 160,49
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to influence business, politics, security, planning and other social aspects. Recently, deep learning techniques have had many successful applications in the AI field. The research presented in this book emerges from the conviction that there is still much progress to be made toward exploiting deep learning in the context of social media data analytics. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis. This work could serve as a good reference for researchers, as well as a compilation of innovative ideas and solutions for practitioners interested in applying deep learning techniques to social media data analytics. 312 pp. Englisch.
Idioma: Inglés
Publicado por Springer, Springer Sep 2022, 2022
ISBN 10: 303110868X ISBN 13: 9783031108686
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 160,49
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to influence business, politics, security, planning and other social aspects. Recently, deep learning techniques have had many successful applications in the AI field. The research presented in this book emerges from the conviction that there is still much progress to be made toward exploiting deep learning in the context of social media data analytics. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis. This work could serve as a good reference for researchers, as well as a compilation of innovative ideas and solutions for practitioners interested in applying deep learning techniques to social media data analytics.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 312 pp. Englisch.