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Record Nr. |
UNINA9910253868203321 |
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Autore |
Biagioni Raoul |
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Titolo |
The SenticNet Sentiment Lexicon: Exploring Semantic Richness in Multi-Word Concepts / / by Raoul Biagioni |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (VI, 55 p. 13 illus., 8 illus. in color.) |
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Collana |
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SpringerBriefs in Cognitive Computation, , 2212-6023 ; ; 4 |
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Disciplina |
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Soggetti |
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Neurosciences |
Natural language processing (Computer science) |
Semantics |
Natural Language Processing (NLP) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters and index. |
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Nota di contenuto |
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Introduction -- Sentiment Analysis -- SenticNet -- Unsupervised Sentiment Classification -- Evaluation -- Conclusion -- Index. . |
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Sommario/riassunto |
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The research and its outcomes presented in this book, is about lexicon-based sentiment analysis. It uses single-, and multi-word concepts from the SenticNet sentiment lexicon as the source of sentiment information for the purpose of sentiment classification. In 6 chapters the book sheds light on the comparison of sentiment classification accuracy between single-word and multi-word concepts, for which a bespoke sentiment analysis system developed by the author was used. This book will be of interest to students, educators and researchers in the field of Sentic Computing. |
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