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The SenticNet Sentiment Lexicon: Exploring Semantic Richness in Multi-Word Concepts / by Raoul Biagioni.
- Format:
- Book
- Author/Creator:
- Biagioni, Raoul, author.
- Series:
- Biomedical and Life Sciences (Springer-11642)
- SpringerBriefs in cognitive computation 2212-6023 ; 4.
- SpringerBriefs in Cognitive Computation, 2212-6023 ; 4
- Language:
- English
- Subjects (All):
- Neurosciences.
- Natural language processing (Computer science).
- Semantics.
- Natural Language Processing (NLP).
- Local Subjects:
- Neurosciences.
- Natural Language Processing (NLP).
- Semantics.
- Physical Description:
- 1 online resource (VI, 55 pages) : 13 illustrations, 8 illustrations in color.
- Edition:
- First edition 2016.
- Contained In:
- Springer eBooks
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2016.
- System Details:
- text file PDF
- Summary:
- 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.
- Contents:
- Introduction
- Sentiment Analysis
- SenticNet
- Unsupervised Sentiment Classification
- Evaluation
- Conclusion
- Index. .
- Other Format:
- Printed edition:
- ISBN:
- 978-3-319-38971-4
- 9783319389714
- Access Restriction:
- Restricted for use by site license.
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