Sentic Computing

Amir Hussain

ISBN 10: 9400750692 / ISBN 13: 9789400750692

Edité par Springer Netherlands, Springer Netherlands Jul 2012, 2012

A propos de cet article

Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 172 pp. Englisch.

N° de réf. du vendeur 9789400750692

Détails bibliographiques

• Titre: Sentic Computing
• Éditeur: Springer Netherlands, Springer Netherlands Jul 2012
• Date de parution: 2012
• Langue: anglais
• ISBN à 10 chiffres: 9400750692
• ISBN à 13 chiffres: 9789400750692
• Reliure: Taschenbuch
• État de l'article: Neu

A propos de ce titre

Synopsis

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.