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March-April 2013 (vol. 28 no. 2)
pp. 12-14
Erik Cambria, National University of Singapore
Bjorn Schuller, Technische Universität München
Bing Liu, University of Illinois at Chicago
Haixun Wang, Microsoft Research Asia
Catherine Havasi, Massachusetts Institute of Technology
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.
Index Terms:
Special issues and sections,Social network services,Data mining,Knowledge discovery,Emotion recognition,User interfaces,Information analysis,Natural language processing,online social data,concept-level sentiment analysis,knowledge mining,data mining,opinion mining,intelligent systems
Citation:
Erik Cambria, Bjorn Schuller, Bing Liu, Haixun Wang, Catherine Havasi, "Knowledge-Based Approaches to Concept-Level Sentiment Analysis," IEEE Intelligent Systems, vol. 28, no. 2, pp. 12-14, March-April 2013, doi:10.1109/MIS.2013.45
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