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020 _a9783319389714
040 _aES-MaUEC
050 4 _aP325.5.D38
_bB534 2016 EB
082 0 4 _a612.8
100 1 _aBiagioni, Raoul
_0Local
_999544
245 1 4 _aThe SenticNet Sentiment Lexicon: Exploring Semantic Richness in Multi-Word Concepts
_cby Raoul Biagioni
260 _aCham
_bSpringer International Publishing
_c2016
300 _a1 recurso en línea (VI, 55 p.)
_b13 ilustraciones, 8 ilustraciones en color
336 _aTexto (visual)
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
490 1 _aSpringerBriefs in Cognitive Computation
_x2212-6023
_v4
505 0 _aIntroduction -- Sentiment Analysis -- SenticNet -- Unsupervised Sentiment Classification -- Evaluation -- Conclusion -- Index. .
520 _aThe 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.
710 2 _aSpringerLink (Online service)
_0Local
_9106996
942 _2lcc
_cLE
988 0 0 _aEBOOK, EBSPRINGER
650 7 _aMedicina
_0comprobar BNE19900959047
_2embne
_9405021
650 7 _aNeurociencias
_0comprobar BNE20012490612
_2embne
_9158907
830 0 _aSpringerBriefs in Cognitive Computation
_x2212-6023
_v4
_9133374
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-38971-4
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901 _ai9783319389714
907 _a.b12953829
_b10-10-17
_c21-11-16
998 _am
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_a_vill
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945 _aP325.5.D38 B534 2016 EB
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