With the current level of ubiquity of social media websites, obtaining online users preferences automatically became a crucial task to assess their tendencies and behaviors online. Arabic language is one of the most spoken languages in the world, and the fastest growing language on the Internet which motivates us to provide automated tools for Arabic language that can perform reliable sentiment analysis to deduct users opinions.In this book, we present our work of Arabic comments sentiments classification based on our collected and manually annotated corpora of YouTube Arabic comments. We share our classification results utilizing several machine learning classifiers: SVM-RBF, linear SVM OAO, linear SVM OAA, Perceptron, Passive Aggressive, SGD, Random Forest, Logistic Regression, Bernoulli NB and KNN.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Esra'a received her M.Sc. degree in Computer Engineering from Jordan University of Science and Technology (JUST) in 2018. Her research interest includes machine learning, deep learning, text analysis, and artificial intelligence (AI).
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -With the current level of ubiquity of social media websites, obtaining online users preferences automatically became a crucial task to assess their tendencies and behaviors online. Arabic language is one of the most spoken languages in the world, and the fastest growing language on the Internet which motivates us to provide automated tools for Arabic language that can perform reliable sentiment analysis to deduct users opinions.In this book, we present our work of Arabic comments sentiments classification based on our collected and manually annotated corpora of YouTube Arabic comments. We share our classification results utilizing several machine learning classifiers: SVM-RBF, linear SVM OAO, linear SVM OAA, Perceptron, Passive Aggressive, SGD, Random Forest, Logistic Regression, Bernoulli NB and KNN. 208 pp. Englisch. Bestandsnummer des Verkäufers 9786202799553
Anzahl: 2 verfügbar
Anbieter: moluna, Greven, Deutschland
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bani Issa Esra aEsra a received her M.Sc. degree in Computer Engineering from Jordan University of Science and Technology (JUST) in 2018. Her research interest includes machine learning, deep learning, text analysis, and artificial i. Bestandsnummer des Verkäufers 493982901
Anzahl: Mehr als 20 verfügbar
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Sentiment Analysis of Arabic YouTube Comments | Esra'a Bani Issa (u. a.) | Taschenbuch | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202799553 | Verantwortliche Person für die EU: LAP Lambert Academic Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 119219927
Anzahl: 5 verfügbar
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -With the current level of ubiquity of social media websites, obtaining online users preferences automatically became a crucial task to assess their tendencies and behaviors online. Arabic language is one of the most spoken languages in the world, and the fastest growing language on the Internet which motivates us to provide automated tools for Arabic language that can perform reliable sentiment analysis to deduct users opinions.In this book, we present our work of Arabic comments sentiments classification based on our collected and manually annotated corpora of YouTube Arabic comments. We share our classification results utilizing several machine learning classifiers: SVM-RBF, linear SVM OAO, linear SVM OAA, Perceptron, Passive Aggressive, SGD, Random Forest, Logistic Regression, Bernoulli NB and KNN.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 208 pp. Englisch. Bestandsnummer des Verkäufers 9786202799553
Anzahl: 1 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - With the current level of ubiquity of social media websites, obtaining online users preferences automatically became a crucial task to assess their tendencies and behaviors online. Arabic language is one of the most spoken languages in the world, and the fastest growing language on the Internet which motivates us to provide automated tools for Arabic language that can perform reliable sentiment analysis to deduct users opinions.In this book, we present our work of Arabic comments sentiments classification based on our collected and manually annotated corpora of YouTube Arabic comments. We share our classification results utilizing several machine learning classifiers: SVM-RBF, linear SVM OAO, linear SVM OAA, Perceptron, Passive Aggressive, SGD, Random Forest, Logistic Regression, Bernoulli NB and KNN. Bestandsnummer des Verkäufers 9786202799553
Anzahl: 1 verfügbar