2012, XVIII, 153 p. 39 illus., 35 illus. in color.
Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.
You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.
After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.
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
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.
Content Level »Research
Keywords »Artificial Intelligence - Cognitive and Affective Modeling - Natural Language Processing - Opinion Mining and Sentiment Analysis