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Sentic ComputingSenticNet

Sentic Computing: SenticNet [SenticNet is the knowledge base which the sentic computing framework leverages on for concept-level sentiment analysis. This chapter illustrates how such a resource is built. In particular, the chapter thoroughly explains the processes of knowledge acquisition, representation, and reasoning, which contribute to the generation of semantics and sentics that form SenticNet. The first part consists of a description of the knowledge sources used. The second part of the chapter illustrates how the collected knowledge is merged and represented redundantly at three levels: semantic network, matrix, and vector space. Finally, the third part presents the graph-mining and dimensionality-reduction techniques used to perform analogical reasoning, emotion recognition, and polarity detection.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Sentic ComputingSenticNet

Part of the Socio-Affective Computing Book Series (volume 1)
Cambria, Erik; Hussain, Amir
Sentic Computing — Aug 19, 2015
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48 pages

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Publisher
Springer International Publishing
Copyright
© Springer International Publishing Switzerland 2015
ISBN
978-3-319-23653-7
Pages
23 –71
DOI
10.1007/978-3-319-23654-4_2
Publisher site
See Chapter on Publisher Site

Abstract

[SenticNet is the knowledge base which the sentic computing framework leverages on for concept-level sentiment analysis. This chapter illustrates how such a resource is built. In particular, the chapter thoroughly explains the processes of knowledge acquisition, representation, and reasoning, which contribute to the generation of semantics and sentics that form SenticNet. The first part consists of a description of the knowledge sources used. The second part of the chapter illustrates how the collected knowledge is merged and represented redundantly at three levels: semantic network, matrix, and vector space. Finally, the third part presents the graph-mining and dimensionality-reduction techniques used to perform analogical reasoning, emotion recognition, and polarity detection.]

Published: Aug 19, 2015

Keywords: Knowledge representation and reasoning; Semantic network; Vector space model; Spreading activation; Emotion categorization

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