04031nam 22006855 450 991029844750332120200629203314.03-319-23654-710.1007/978-3-319-23654-4(CKB)3430000000002619(EBL)4198396(SSID)ssj0001596904(PQKBManifestationID)16296846(PQKBTitleCode)TC0001596904(PQKBWorkID)14886473(PQKB)11545548(DE-He213)978-3-319-23654-4(MiAaPQ)EBC4198396(PPN)190884371(EXLCZ)99343000000000261920151210d2015 u| 0engur|n|---|||||txtccrSentic Computing A Common-Sense-Based Framework for Concept-Level Sentiment Analysis /by Erik Cambria, Amir Hussain1st ed. 2015.Cham :Springer International Publishing :Imprint: Springer,2015.1 online resource (196 p.)Socio-Affective Computing,2509-5706 ;1Description based upon print version of record.3-319-23653-9 Includes bibliographical references and index.Introduction -- SenticNet -- Sentic Patterns -- Sentic Applications -- Conclusion -- Index.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.Socio-Affective Computing,2509-5706 ;1NeurosciencesData miningSemanticsCognitive psychologyNeuroscienceshttps://scigraph.springernature.com/ontologies/product-market-codes/B18006Data Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Semanticshttps://scigraph.springernature.com/ontologies/product-market-codes/N39000Cognitive Psychologyhttps://scigraph.springernature.com/ontologies/product-market-codes/Y20060Neurosciences.Data mining.Semantics.Cognitive psychology.Neurosciences.Data Mining and Knowledge Discovery.Semantics.Cognitive Psychology.610Cambria Erikauthttp://id.loc.gov/vocabulary/relators/aut885028Hussain Amirauthttp://id.loc.gov/vocabulary/relators/autBOOK9910298447503321Sentic Computing2519135UNINA