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Title: OntoSenticNet : a commonsense ontology for sentiment analysis
Authors: Dragoni, Mauro
Poria, Soujanya
Cambria, Erik
Keywords: Engineering::Computer science and engineering
Issue Date: 2018
Source: Dragoni, M., Poria, S., & Cambria, E. (2018). OntoSenticNet : a commonsense ontology for sentiment analysis. 33(3), 77-85. doi:10.1109/MIS.2018.033001419
Journal: IEEE Intelligent Systems
Abstract: In this work, we present OntoSenticNet, a commonsense ontology for sentiment analysis based on SenticNet, a semantic network of 100,000 concepts based on conceptual primitives. The key characteristics of OntoSenticNet are: (i) the definition of precise conceptual hierarchy and properties associating concepts and sentiment values; (ii) the support for connecting external information (e.g., word embedding, domain information, and different polarity representations) to each individual defined within the ontology; and (iii) the capability of associating each concept with annotations contained in external resources (e.g., documents and multimodal resources).
ISSN: 1541-1672
DOI: 10.1109/MIS.2018.033001419
Rights: © 2018 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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