Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Jun 2023, 2023
ISBN 10: 6206183556 ISBN 13: 9786206183556
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 43,90
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Neuware -Code-mixed language is very commonly used in today¿s multilingual society. It is the phenomenon of mixing the syntax and vocabulary of many languages in single sentence. Sentiment analysis of code-mixed language aims at identifying the polarity value of the sentence. This book mainly focuses on sentiment analysis of code-mixed Tweets consisting of words from Hindi and English language and it also contains other symbols. The developed system is used to detect the polarity/sentiment value of a tweet where the value of polarity can be positive, negative or neutral. Various experiments are carried out on a dataset of Tweets using different models. Results of different models are evaluated and compared.Books on Demand GmbH, Überseering 33, 22297 Hamburg 84 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206183556 ISBN 13: 9786206183556
Librería: preigu, Osnabrück, Alemania
EUR 39,35
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Sentiment Analysis of Code-Mixed Language | Sukhpreet Kaur | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206183556 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Jun 2023, 2023
ISBN 10: 6206183556 ISBN 13: 9786206183556
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 43,90
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Code-mixed language is very commonly used in today's multilingual society. It is the phenomenon of mixing the syntax and vocabulary of many languages in single sentence. Sentiment analysis of code-mixed language aims at identifying the polarity value of the sentence. This book mainly focuses on sentiment analysis of code-mixed Tweets consisting of words from Hindi and English language and it also contains other symbols. The developed system is used to detect the polarity/sentiment value of a tweet where the value of polarity can be positive, negative or neutral. Various experiments are carried out on a dataset of Tweets using different models. Results of different models are evaluated and compared. 84 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206183556 ISBN 13: 9786206183556
Librería: moluna, Greven, Alemania
EUR 35,62
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kaur SukhpreetSukhpreet Kaur has completed her MPhil from Department of Computer Science, Punjabi University, Patiala. She is NET qualified and currently working as Assistant Programmer in Jagat Guru Nanak Dev Punjab State Open Unive.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206183556 ISBN 13: 9786206183556
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 44,59
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Code-mixed language is very commonly used in today's multilingual society. It is the phenomenon of mixing the syntax and vocabulary of many languages in single sentence. Sentiment analysis of code-mixed language aims at identifying the polarity value of the sentence. This book mainly focuses on sentiment analysis of code-mixed Tweets consisting of words from Hindi and English language and it also contains other symbols. The developed system is used to detect the polarity/sentiment value of a tweet where the value of polarity can be positive, negative or neutral. Various experiments are carried out on a dataset of Tweets using different models. Results of different models are evaluated and compared.