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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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Successes and challenges in developing a hybrid approach to sentiment analysis
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Abstract:
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. ; This article covers some success and learning experiences attained during the developing of a hybrid approach to Sentiment Analysis (SA) based on a Sentiment Lexicon, Semantic Rules, Negation Handling, Ambiguity Management and Linguistic Variables. The proposed hybrid method is presented and applied to two selected datasets: Movie Review and Sentiment Twitter datasets. The achieved results are compared against those obtained when Nai ve Bayes (NB) and Maximum Entropy (ME) supervised machine learning classification methods are used for the same datasets. The proposed hybrid system attained higher accuracy and precision scores than NB and ME, which shows its superiority when applied to the SA problem at the sentence level. Finally, an alternative strategy to calculating the orientation polarity and polarity intensity in one step instead of the two steps method used in the hybrid approach is explored. The analysis of the yielded mixed results achieved with this alternative approach shows its potential as an aid in the computation of semantic orientations and produced some lessons learnt in developing a more effective mechanism to calculating the orientation polarity and polarity intensity.
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Keyword:
Computational linguistic; Computing with Sentiments; Fuzzy sets; Natural language processing; Sentiment Analysis; Sentiment rules; SentiWordNet; Uninorms
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URL: https://doi.org/10.1007/s10489-017-0966-4 http://hdl.handle.net/2086/14154
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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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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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40 |
A Hybrid Approach to the Sentiment Analysis Problem at the Sentence Level
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