Sentic Computing
Techniques, Tools, and Applications
Authors: Cambria, Erik, Hussain, Amir
Free Preview- Represents the first comprehensive review of Sentic Computing, state-of-the-art approach to opinion mining and sentiment analysis (see http://en.wikipedia.org/wiki/Sentiment_analysis)
- A special chapter on cognitive and affective modeling for natural language understanding
- Includes tips on different strategies (techniques, online resources, datasets, etc.) to opinion mining and sentiment analysis
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- About this book
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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.
- Table of contents (6 chapters)
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Introduction
Pages 1-10
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Background
Pages 11-33
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Techniques
Pages 35-67
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Tools
Pages 69-101
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Applications
Pages 103-146
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Table of contents (6 chapters)
- Download Preface 1 PDF (51.2 KB)
- Download Sample pages 2 PDF (382.8 KB)
- Download Table of contents PDF (93.8 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Sentic Computing
- Book Subtitle
- Techniques, Tools, and Applications
- Authors
-
- Erik Cambria
- Amir Hussain
- Series Title
- SpringerBriefs in Cognitive Computation
- Series Volume
- 2
- Copyright
- 2012
- Publisher
- Springer Netherlands
- Copyright Holder
- The Author(s)
- eBook ISBN
- 978-94-007-5070-8
- DOI
- 10.1007/978-94-007-5070-8
- Softcover ISBN
- 978-94-007-5069-2
- Series ISSN
- 2212-6023
- Edition Number
- 1
- Number of Pages
- XVIII, 153
- Number of Illustrations
- 4 b/w illustrations, 35 illustrations in colour
- Topics
