Band 1
Sentic Computing A Common-Sense-Based Framework for Concept-Level Sentiment Analysis
Aus der Reihe
Socio-Affective Computing
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- Hardcover
- Taschenbuch
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Form:Einzelkauf Download
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Sprache:Englisch
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Verlag:Springer
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98,99 €
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Produktdetails
Format
Kopierschutz
Nein
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
11.12.2015
Verlag
SpringerSeitenzahl
176 (Printausgabe)
Dateigröße
4423 KB
Sprache
Englisch
EAN
9783319236544
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 andsystems.
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 andsystems.
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