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The SenticNet sentiment lexicon = ex...
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SpringerLink (Online service)
The SenticNet sentiment lexicon = exploring semantic richness in multi-word concepts /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
The SenticNet sentiment lexicon/ by Raoul Biagioni.
Reminder of title:
exploring semantic richness in multi-word concepts /
Author:
Biagioni, Raoul.
Published:
Cham :Springer International Publishing : : 2016.,
Description:
vi, 55 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Semantics - Data processing. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-38971-4
ISBN:
9783319389714
The SenticNet sentiment lexicon = exploring semantic richness in multi-word concepts /
Biagioni, Raoul.
The SenticNet sentiment lexicon
exploring semantic richness in multi-word concepts /[electronic resource] :by Raoul Biagioni. - Cham :Springer International Publishing :2016. - vi, 55 p. :ill., digital ;24 cm. - SpringerBriefs in cognitive computation,v.42212-6023 ;. - SpringerBriefs in cognitive computation ;2..
Introduction -- Sentiment Analysis -- SenticNet -- Unsupervised Sentiment Classification -- Evaluation -- Conclusion -- Index.
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.
ISBN: 9783319389714
Standard No.: 10.1007/978-3-319-38971-4doiSubjects--Topical Terms:
675131
Semantics
--Data processing.
LC Class. No.: P325.5.D38 / B53 2016
Dewey Class. No.: 006.35
The SenticNet sentiment lexicon = exploring semantic richness in multi-word concepts /
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Introduction -- Sentiment Analysis -- SenticNet -- Unsupervised Sentiment Classification -- Evaluation -- Conclusion -- Index.
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Biomedical and Life Sciences (Springer-11642)
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