Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis Softcover Repri Edition Contributor(s): Cambria, Erik (Author), Hussain, Amir (Author) |
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ISBN: 3319795163 ISBN-13: 9783319795164 Publisher: Springer OUR PRICE: $104.49 Product Type: Paperback - Other Formats Published: March 2019 |
Additional Information |
BISAC Categories: - Medical | Neuroscience - Computers | Databases - Data Mining - Language Arts & Disciplines | Linguistics - Semantics |
Dewey: 006 |
Series: Socio-Affective Computing |
Physical Information: 176 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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. |