Sentic Computing

Techniques, Tools, and Applications

  • Erik Cambria
  • Amir Hussain

Part of the SpringerBriefs in Cognitive Computation book series (BRIEFSCC, volume 2)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Erik Cambria, Amir Hussain
    Pages 1-10
  3. Erik Cambria, Amir Hussain
    Pages 11-33
  4. Erik Cambria, Amir Hussain
    Pages 35-67
  5. Erik Cambria, Amir Hussain
    Pages 69-101
  6. Erik Cambria, Amir Hussain
    Pages 103-146
  7. Erik Cambria, Amir Hussain
    Pages 147-153

About this book


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.


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

Authors and affiliations

  • Erik Cambria
    • 1
  • Amir Hussain
    • 2
  1. 1., Media LaboratoryMassachusetts Institute of TechnologyCambridgeUSA
  2. 2.Dept. Computing ScienceUniversity of StirlingStirlingUnited Kingdom

Bibliographic information

  • DOI
  • Copyright Information The Author(s) 2012
  • Publisher Name Springer, Dordrecht
  • eBook Packages Biomedical and Life Sciences
  • Print ISBN 978-94-007-5069-2
  • Online ISBN 978-94-007-5070-8
  • Series Print ISSN 2212-6023
  • Series Online ISSN 2212-6031
  • Buy this book on publisher's site
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