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The SenticNet sentiment lexicon[elec...

Biagioni, Raoul.

The SenticNet sentiment lexicon[electronic resource] :exploring semantic richness in multi-word concepts /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.35
書名/作者:	The SenticNet sentiment lexicon : exploring semantic richness in multi-word concepts // by Raoul Biagioni.
作者:	Biagioni, Raoul.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	vi, 55 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Semantics - Data processing.
標題:	Computational linguistics.
標題:	Biomedicine.
標題:	Neurosciences.
標題:	Language Translation and Linguistics.
標題:	Semantics.
ISBN:	9783319389714
ISBN:	9783319389707
內容註:	Introduction -- Sentiment Analysis -- SenticNet -- Unsupervised Sentiment Classification -- Evaluation -- Conclusion -- Index.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-38971-4

The SenticNet sentiment lexicon[electronic resource] :exploring semantic richness in multi-word concepts /
Biagioni, Raoul.

The SenticNet sentiment lexiconexploring 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 ;5..

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:

518016
Semantics
--Data processing.

LC Class. No.: P325.5.D38 / B53 2016

Dewey Class. No.: 006.35

The SenticNet sentiment lexicon[electronic resource] :exploring semantic richness in multi-word concepts /
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