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Sentic Computing Techniques Tools by Cambria Erik (8 results)
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Sentic Computing: Techniques, Tools, and Applications (SpringerBriefs in Cognitive Computation, 2)
Seller: Zubal-Books, Since 1961, Cleveland, OH, U.S.A.
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Sentic Computing: Techniques, Tools, and Applications (SpringerBriefs in Cognitive Computation, 2)
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Paperback or Softback. Condition: New. Sentic Computing: Techniques, Tools, and Applications. Book.
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Add to basketPaperback. Condition: Brand New. 1st edition. 153 pages. 9.00x6.50x0.50 inches. In Stock.
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Taschenbuch. Condition: Neu. Sentic Computing | Techniques, Tools, and Applications | Erik Cambria (u. a.) | Taschenbuch | SpringerBriefs in Cognitive Computation | xviii | Englisch | 2012 | Springer | EAN 9789400750692 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality reduction techniques is exploited on two common sense knowledge bases to develop a novel intelligent engine for open-domain opinion mining and sentiment analysis. The proposed approach, termed sentic computing, performs a clause-level semantic analysis of text, which allows the inference of both the conceptual and emotional information associated with natural language opinions and, hence, a more efficient passage from (unstructured) textual information to (structured) machine-processable data.
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Sentic Computing : Techniques, Tools, and Applications
Language: English
Published by Springer Netherlands, 2012
ISBN 10: 9400750692 ISBN 13: 9789400750692
Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | In this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality reduction techniques is exploited on two common sense knowledge bases to develop a novel intelligent engine for open-domain opinion mining and sentiment analysis. The proposed approach, termed sentic computing, performs a clause-level semantic analysis of text, which allows the inference of both the conceptual and emotional information associated with natural language opinions and, hence, a more efficient passage from (unstructured) textual information to (structured) machine-processable data.
