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Autor(en): 
  • Amir Hussain
  • Erik Cambria
  • Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  März 2019  
    Genre:  Naturwissensch., Medizin, Technik 
     
    B / Biomedical and Life Sciences / Cognition & cognitive psychology / cognitive psychology / Data Mining / Data Mining and Knowledge Discovery / Expert systems / knowledge-based systems / Kognitive Psychologie
    ISBN:  9783319795164 
    EAN-Code: 
    9783319795164 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #01 - Socio-Affective Computing  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  424 gr 
    Seiten:  176 
    Illustration:  XXII, 176 p. 54 illus., 40 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.
      



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