Sentic Computing :
Cambria, Erik.
Sentic Computing : Techniques, Tools, and Applications / by Erik Cambria, Amir Hussain. - xviii, 153 páginas 39 ilustraciones, 35 ilustraciones en color. recurso en línea. - SpringerBriefs in Cognitive Computation, 2 2212-6023 ; .
Springer eBooks
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.
9789400750708
10.1007/9789400750708 doi
R-RZ
Sentic Computing : Techniques, Tools, and Applications / by Erik Cambria, Amir Hussain. - xviii, 153 páginas 39 ilustraciones, 35 ilustraciones en color. recurso en línea. - SpringerBriefs in Cognitive Computation, 2 2212-6023 ; .
Springer eBooks
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.
9789400750708
10.1007/9789400750708 doi
R-RZ