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Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis (in English)
Erik Cambria
(Author)
·
Amir Hussain
(Author)
·
Springer
· Hardcover
Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis (in English) - Cambria, Erik ; Hussain, Amir
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Synopsis "Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis (in English)"
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 clausesThis 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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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
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