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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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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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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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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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Abstract:
The objective of this article is two-fold. Firstly, a hybrid approach to Sentiment Analysis encompassing the use of Semantic Rules, Fuzzy Sets and an enriched Sentiment Lexicon, improved with the support of SentiWordNet is described. Secondly, the proposed hybrid method is compared against two well established Supervised Learning techniques, Naïve Bayes and Maximum Entropy. Using the well known and publicly available Movie Review Dataset, the proposed hybrid system achieved higher accuracy and precision than Naïve Bayes (NB) and Maximum Entropy (ME).
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Keyword:
Computational Linguistic; Fuzzy Sets; Natural Language Processing; Semantic Rules; Sentiment Analysis; SentiWordNet
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URL: http://hdl.handle.net/2086/11859
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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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