Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203306207 ISBN 13: 9786203306200
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing 2021-01-25, 2021
ISBN 10: 6203306207 ISBN 13: 9786203306200
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Aggiungi al carrelloPaperback. Condizione: New.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203306207 ISBN 13: 9786203306200
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Efficient Techniques for Sentiment Analysis from Social Media Data | Savitha Hiremath (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203306200 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203306207 ISBN 13: 9786203306200
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203306207 ISBN 13: 9786203306200
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Aggiungi al carrelloPAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Jan 2021, 2021
ISBN 10: 6203306207 ISBN 13: 9786203306200
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The enormous growth of Internet usage, number of social interactions, and activities in social networking sites has resulted in users adding their opinions on products, events, etc., However, due to a large amount of user-generated data, it is an expensive process to analyze the data manually. Sentiment Classifiers are used for automated analysis to extract sentiments and opinions conveyed in the user-comments. The Book includes insight into various efficient techniques for Sentiment Analysis and Opinion Mining from Social Media Data. All algorithms discussed give better Accuracy of sentiment classification. 208 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203306207 ISBN 13: 9786203306200
Da: moluna, Greven, Germania
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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: Hiremath SavithaDr. Savitha Hiremath, currently working as an Assistant Professor in the Department of ISE at CMR Institute of Technology, Bengaluru.Dr. S H Manjula is a Professor in the Department of CSE at UVCE, Bangalore Universit.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Jan 2021, 2021
ISBN 10: 6203306207 ISBN 13: 9786203306200
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The enormous growth of Internet usage, number of social interactions, and activities in social networking sites has resulted in users adding their opinions on products, events, etc., However, due to a large amount of user-generated data, it is an expensive process to analyze the data manually. Sentiment Classifiers are used for automated analysis to extract sentiments and opinions conveyed in the user-comments. The Book includes insight into various efficient techniques for Sentiment Analysis and Opinion Mining from Social Media Data. All algorithms discussed give better Accuracy of sentiment classification.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 208 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203306207 ISBN 13: 9786203306200
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 72,76
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The enormous growth of Internet usage, number of social interactions, and activities in social networking sites has resulted in users adding their opinions on products, events, etc., However, due to a large amount of user-generated data, it is an expensive process to analyze the data manually. Sentiment Classifiers are used for automated analysis to extract sentiments and opinions conveyed in the user-comments. The Book includes insight into various efficient techniques for Sentiment Analysis and Opinion Mining from Social Media Data. All algorithms discussed give better Accuracy of sentiment classification.