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Please use this identifier to cite or link to this item: https://doi.org/10.1109/MIS.2013.45
Title: Knowledge-based approaches to concept-level sentiment analysis
Authors: Cambria, E. 
Schuller, B.
Liu, B.
Wang, H.
Havasi, C.
Keywords: concept-level sentiment analysis
data mining
intelligent systems
knowledge mining
online social data
opinion mining
Issue Date: 2013
Citation: Cambria, E., Schuller, B., Liu, B., Wang, H., Havasi, C. (2013). Knowledge-based approaches to concept-level sentiment analysis. IEEE Intelligent Systems 28 (2) : 12-14. ScholarBank@NUS Repository. https://doi.org/10.1109/MIS.2013.45
Abstract: The guest editors introduce novel approaches to opinion mining and sentiment analysis that go beyond a mere word-level analysis of text and provide concept-level methods. Such approaches allow a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain. © 2001-2011 IEEE.
Source Title: IEEE Intelligent Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/116880
ISSN: 15411672
DOI: 10.1109/MIS.2013.45
Appears in Collections:Staff Publications

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