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A T1OWA Fuzzy Linguistic Aggregation Methodology for Searching Feature-based Opinions.
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Dealing with Incomplete Information in Linguistic Group Decision Making by Means of Interval Type-2 Fuzzy Sets
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An overview on managing additive consistency of reciprocal preference relations for consistency-driven decision making and Fusion: Taxonomy and future directions
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Flexible inverse adaptive fuzzy inference model to identify the evolution of Operational Value at Risk for improving operational risk management
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A fuzzy credibility model to estimate the operational value at risk using internal and external data of risk events
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Preference similarity network structural equivalence clustering based consensus group decision making model
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A consensus approach to sentiment analysis
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Abstract:
There are many situations where the opinion of the majority of participants is critical. The scenarios could be multiple, like a number of doctors finding commonality on the diagnosing of an illness or parliament members looking for consensus on a specific law being passed. In this article we present a method that utilises Induced Ordered Weighted Averaging (IOWA) operators to aggregate a majority opinion from a number of Sentiment Analysis (SA) classification systems, where the latter occupy the role usually taken by human decision-makers. Previously determined sentence intensity polarity by different SA classification methods are used as input to a specific IOWA operator. During the experimental phase, the use of the IOWA operator coupled with the linguistic quantifier `most' (IOWA_most) proved to yield superior results compared to those achieved when utilising other techniques commonly applied when some sort of averaging is needed, such as arithmetic mean or median techniques.
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Keyword:
Consensus; Hybrid Sentiment Analysis Method; IOWA operaor; Majority Support; Maximum Entropy; Naïve Bayes; Sentiment Aggregation
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URL: https://doi.org/10.1007/978-3-319-60042-0_69 http://hdl.handle.net/2086/13366
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28 |
An interaction consensus in group decision making under distributed trust information
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29 |
Successes and challenges in developing a hybrid approach to sentiment analysis
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A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust
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A consensus approach to the sentiment analysis problem driven by support-based IOWA majority
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32 |
Type-1 OWA Unbalanced Fuzzy Linguistic Aggregation Methodology. Application to Eurobonds Credit Risk Evaluation
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Preference Similarity Network Structural Equivalence Clustering based Consensus Model
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Linguistic multi-criteria decision-making model with output variable expressive richness
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35 |
Successes and challenges in developing a hybrid approach to sentiment analysis
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A Consensus Approach to the Sentiment Analysis Problem Driven by Support-Based IOWA Majority
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A Hybrid Approach to Sentiment Analysis with Benchmarking Results
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A new consensus measure based on Pearson correlation coefficient
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A Hybrid Approach to the Sentiment Analysis Problem at the Sentence Level
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