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Citation

Cambria E & Hussain A (2012) Sentic Computing: Techniques, Tools, and Applications. SpringerBriefs in Cognitive Computation, 2. Dordrecht: Springer. http://link.springer.com/book/10.1007/978-94-007-5070-8/page/1#

Abstract
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.

Keywords
Artificial Intelligence; Cognitive and Affective Modeling; Natural Language Processing; Opinion Mining and Sentiment Analysis