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Aggiungi al carrelloCondizione: New. pp. 256.
Lingua: Inglese
Editore: Morgan Kaufmann 2016-09-16, 2016
ISBN 10: 0128044128 ISBN 13: 9780128044124
Da: Chiron Media, Wallingford, Regno Unito
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Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: Elsevier Science & Technology, 2016
ISBN 10: 0128044128 ISBN 13: 9780128044124
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
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Aggiungi al carrelloCondizione: New. In.
Lingua: Inglese
Editore: Morgan Kaufmann 2016-09-16, 2016
ISBN 10: 0128044128 ISBN 13: 9780128044124
Da: Chiron Media, Wallingford, Regno Unito
EUR 62,59
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Aggiungi al carrelloPaperback. Condizione: New.
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Aggiungi al carrelloCondizione: New. Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network mining S.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Sentiment Analysis in Social Networks | Federico Alberto Pozzi (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2016 | Morgan Kaufmann | EAN 9780128044124 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
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Da: Revaluation Books, Exeter, Regno Unito
EUR 51,04
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Aggiungi al carrelloPaperback. Condizione: Brand New. 284 pages. 9.25x7.25x1.00 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: Elsevier Science & Technology, 2016
ISBN 10: 0128044128 ISBN 13: 9780128044124
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 76,65
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Aggiungi al carrelloPaperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 96,14
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network analysis Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics.
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 150,00
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network analysis Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics Englisch.