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| Autore: |
Cambria Erik
|
| Titolo: |
Sentic Computing : A Common-Sense-Based Framework for Concept-Level Sentiment Analysis / / by Erik Cambria, Amir Hussain
|
| Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Edizione: | 1st ed. 2015. |
| Descrizione fisica: | 1 online resource (196 p.) |
| Disciplina: | 610 |
| Soggetto topico: | Neurosciences |
| Data mining | |
| Semantics | |
| Cognitive psychology | |
| Data Mining and Knowledge Discovery | |
| Cognitive Psychology | |
| Persona (resp. second.): | HussainAmir |
| Note generali: | Description based upon print version of record. |
| Nota di bibliografia: | Includes bibliographical references and index. |
| Nota di contenuto: | Introduction -- SenticNet -- Sentic Patterns -- Sentic Applications -- Conclusion -- Index. |
| Sommario/riassunto: | 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. |
| Titolo autorizzato: | Sentic Computing ![]() |
| ISBN: | 3-319-23654-7 |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910298447503321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |