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02380nam a22004815i 4500 |
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978-3-319-38971-4 |
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DE-He213 |
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|a 9783319389714
|9 978-3-319-38971-4
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|a 10.1007/978-3-319-38971-4
|2 doi
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|a RC321-580
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|a MED057000
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|a 612.8
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|a Biagioni, Raoul.
|e author.
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|a The SenticNet Sentiment Lexicon: Exploring Semantic Richness in Multi-Word Concepts
|h [electronic resource] /
|c by Raoul Biagioni.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2016.
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| 300 |
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|a VI, 55 p. 13 illus., 8 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
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|a text file
|b PDF
|2 rda
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|a SpringerBriefs in Cognitive Computation,
|x 2212-6023 ;
|v 4
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|a Introduction -- Sentiment Analysis -- SenticNet -- Unsupervised Sentiment Classification -- Evaluation -- Conclusion -- Index. .
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|a 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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|a Medicine.
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|a Neurosciences.
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|a Computational linguistics.
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|a Semantics.
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|a Biomedicine.
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|a Neurosciences.
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|a Language Translation and Linguistics.
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|a Semantics.
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| 710 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783319389707
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| 830 |
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|a SpringerBriefs in Cognitive Computation,
|x 2212-6023 ;
|v 4
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|u http://dx.doi.org/10.1007/978-3-319-38971-4
|z Full Text via HEAL-Link
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|a ZDB-2-SBL
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|a Biomedical and Life Sciences (Springer-11642)
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