Journal
NEURAL COMPUTING & APPLICATIONS
Volume 22, Issue 3-4, Pages 479-489Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00521-012-0853-1
Keywords
Sentiment prediction; Extreme learning machine; OS-ELM; ensemble learning; Intuitionistic fuzzy set; Induced aggregation operator
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Funding
- University Science Research Project of Jiangsu Province [11KJD630001]
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Predicting consumer sentiments revealed in online reviews is crucial to suppliers and potential consumers. We combine online sequential extreme learning machines (OS-ELMs) and intuitionistic fuzzy sets to predict consumer sentiments and propose a generalized ensemble learning scheme. The outputs of OS-ELMs are equivalently transformed into an intuitionistic fuzzy matrix. Then, predictions are made by fusing the degree of membership and non-membership concurrently. Moreover, we implement ELM, OS-ELM, and the proposed fusion scheme for Chinese reviews sentiment prediction. The experimental results have clearly shown the effectiveness of the proposed scheme and the strategy of weighting and order inducing.
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