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. <BR>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.<BR> <BR>READERS WILL DISCOVER THE FOLLOWING KEY NOVELTIES, THAT MAKE THIS APPROACH SO UNIQUE AND AVANT-GARDE, BEING REVIEWED AND DISCUSSED:<BR>· SENTIC COMPUTING'S MULTI-DISCIPLINARY APPROACH TO SENTIMENT ANALYSIS-EVIDENCED BY THE CONCOMITANT USE OF AI, LINGUISTICS AND PSYCHOLOGY FOR KNOWLEDGE REPRESENTATION AND INFERENCE<BR>· 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<BR>· 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<BR><BR />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.
"Sinopsis" puede pertenecer a otra edición de este libro.
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.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. First approach to sentiment analysis that merges AI, linguistics, and psychologyComprehensive explanation of popular sentic computing techniquesFull set of linguistic patterns for sentiment analysisDownloadable knowledge base. Nº de ref. del artículo: 43799534
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 and systems. 200 pp. Englisch. Nº de ref. del artículo: 9783319236537
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783319236537
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Hardcover. Condición: new. Hardcover. 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 Computings 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. Sentic Computing Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783319236537
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