Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200080410 ISBN 13: 9786200080417
Da: Books Puddle, New York, NY, U.S.A.
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200080410 ISBN 13: 9786200080417
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Aggiungi al carrelloPaperback. Condizione: Brand New. 60 pages. 8.66x5.91x0.14 inches. In Stock.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200080410 ISBN 13: 9786200080417
Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Hybrid Data Mining Approach For Emotion Analysis | On Social Network Data | Vadivel Ganesan (u. a.) | Taschenbuch | 60 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200080417 | 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 Apr 2019, 2019
ISBN 10: 6200080410 ISBN 13: 9786200080417
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 -Social media plays a significant role in exploring opinions and emotions of the users based on day to day activities. Mining social network data regarding user's opinions and emotions is necessary to understand the user's behaviour and mentality. This research work proposes a hybrid data mining approach using K-Means clustering and Naive Bayes classification techniques to analyse the emotions in the tweets. Emotion type based classification and Cluster based classification process performed on the tweet emotion data set using Naïve Bayes classifier analyses the performance of the hybrid data mining approach using performance measures. 60 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200080410 ISBN 13: 9786200080417
Da: Majestic Books, Hounslow, Regno Unito
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200080410 ISBN 13: 9786200080417
Da: Biblios, Frankfurt am main, HESSE, Germania
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200080410 ISBN 13: 9786200080417
Da: moluna, Greven, Germania
EUR 34,25
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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: Ganesan VadivelVadivel Ganesan is Assistant Professor and has six years of teaching experience in SNMV College of Arts & Science. He guided & produced two M.Phil Scholars. He attended various faculty development programs. He particip.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Apr 2019, 2019
ISBN 10: 6200080410 ISBN 13: 9786200080417
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 -Social media plays a significant role in exploring opinions and emotions of the users based on day to day activities. Mining social network data regarding user's opinions and emotions is necessary to understand the user's behaviour and mentality. This research work proposes a hybrid data mining approach using K-Means clustering and Naive Bayes classification techniques to analyse the emotions in the tweets. Emotion type based classification and Cluster based classification process performed on the tweet emotion data set using Naïve Bayes classifier analyses the performance of the hybrid data mining approach using performance measures.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200080410 ISBN 13: 9786200080417
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 40,89
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Social media plays a significant role in exploring opinions and emotions of the users based on day to day activities. Mining social network data regarding user's opinions and emotions is necessary to understand the user's behaviour and mentality. This research work proposes a hybrid data mining approach using K-Means clustering and Naive Bayes classification techniques to analyse the emotions in the tweets. Emotion type based classification and Cluster based classification process performed on the tweet emotion data set using Naïve Bayes classifier analyses the performance of the hybrid data mining approach using performance measures.