Cambria, Erik.
Sentic Computing Techniques, Tools, and Applications / [electronic resource] : by Erik Cambria, Amir Hussain. - XVIII, 153 p. 39 illus., 35 illus. in color. online resource. - SpringerBriefs in Cognitive Computation, 2 2212-6023 ; . - SpringerBriefs in Cognitive Computation, 2 .
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
10.1007/978-94-007-5070-8 doi
Medicine.
Data mining.
Mathematics.
Consciousness.
Biomedicine.
Biomedicine general.
Data Mining and Knowledge Discovery.
Mathematics, general.
Linguistics (general).
Cognitive Psychology.
R-RZ
610
Sentic Computing Techniques, Tools, and Applications / [electronic resource] : by Erik Cambria, Amir Hussain. - XVIII, 153 p. 39 illus., 35 illus. in color. online resource. - SpringerBriefs in Cognitive Computation, 2 2212-6023 ; . - SpringerBriefs in Cognitive Computation, 2 .
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
10.1007/978-94-007-5070-8 doi
Medicine.
Data mining.
Mathematics.
Consciousness.
Biomedicine.
Biomedicine general.
Data Mining and Knowledge Discovery.
Mathematics, general.
Linguistics (general).
Cognitive Psychology.
R-RZ
610