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Sentic Computing = A Common-Sense-Based Framework for Concept-Level Sentiment Analysis /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Sentic Computing/ by Erik Cambria, Amir Hussain.
Reminder of title:	A Common-Sense-Based Framework for Concept-Level Sentiment Analysis /
Author:	Cambria, Erik.
other author:	Hussain, Amir.
Description:	XXII, 176 p. 54 illus., 40 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Neurosciences. -
Online resource:	https://doi.org/10.1007/978-3-319-23654-4
ISBN:	9783319236544

Sentic Computing = A Common-Sense-Based Framework for Concept-Level Sentiment Analysis /
Cambria, Erik.

Sentic ComputingA Common-Sense-Based Framework for Concept-Level Sentiment Analysis /[electronic resource] :by Erik Cambria, Amir Hussain. - 1st ed. 2015. - XXII, 176 p. 54 illus., 40 illus. in color.online resource. - Socio-Affective Computing,12509-5706 ;. - Socio-Affective Computing,1.

Introduction -- SenticNet -- Sentic Patterns -- Sentic Applications -- Conclusion -- Index.

This volume presents a knowledge-based approach to concept-level sentiment analysis at the crossroads between affective computing, information extraction, and common-sense computing, which exploits both computer and social sciences to better interpret and process information on the Web. Concept-level sentiment analysis goes beyond a mere word-level analysis of text in order to enable a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain. Readers will discover the following key novelties, that make this approach so unique and avant-garde, being reviewed and discussed: • Sentic Computing's multi-disciplinary approach to sentiment analysis-evidenced by the concomitant use of AI, linguistics and psychology for knowledge representation and inference • Sentic Computing’s shift from syntax to semantics-enabled by the adoption of the bag-of-concepts model instead of simply counting word co-occurrence frequencies in text • Sentic Computing's shift from statistics to linguistics-implemented by allowing sentiments to flow from concept to concept based on the dependency relation between clauses This volume is the first in the Series Socio-Affective Computing edited by Dr Amir Hussain and Dr Erik Cambria and will be of interest to researchers in the fields of socially intelligent, affective and multimodal human-machine interaction and systems.

ISBN: 9783319236544

Standard No.: 10.1007/978-3-319-23654-4doiSubjects--Topical Terms:

593561
Neurosciences.

LC Class. No.: RC321-580

Dewey Class. No.: 612.8

Sentic Computing = A Common-Sense-Based Framework for Concept-Level Sentiment Analysis /
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