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.
