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An Intelligent Group Decision Evaluation Model with Interval-Valued Intuitionistic Fuzzy Entropy Technology for Microblog User Influence
2020
Wireless Communications and Mobile Computing
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' influence into interval-valued intuitionistic fuzzy multiattribute group decision-making problem. ...
Aiming at the shortcomings of some existing interval-valued intuitionistic fuzzy entropy, this paper proposes an interval-valued intuitionistic fuzzy entropy, which contains not only the interval distance ...
The interval intuitionistic fuzzy multiattribute group decision-making method combines interval intuitionistic fuzzy theory with multiattribute group decision-making. ...
doi:10.1155/2020/6646808
fatcat:flovlwdlerbhljjcbsci67cgqe
An overview on the roles of fuzzy set techniques in big data processing: Trends, challenges and opportunities
2017
Knowledge-Based Systems
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In the era of big data, we are facing with an immense volume and high velocity of data with complex structures. ...
A proper processing of big data can result in informative, intelligent and relevant decision making completed in various areas, such as medical and healthcare, business, management and government. ...
Acknowledgments The authors would like to thank the Editor-in-Chief and four anonymous reviewers for their insightful and constructive commendations that have led to an improved version of this paper. ...
doi:10.1016/j.knosys.2016.11.008
fatcat:i2ay7ugn5rfkhmz7jw6hyc67fm
Sentiment Analysis Technique and Neutrosophic Set Theory for Mining and Ranking Big Data From Online Reviews
2021
IEEE Access
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ACKNOWLEDGMENT This work was supported by the Center for Research Excellence and Incubation Management (CREIM) and the Faculty of Informatics and Computing at the University Sultan Zainal Abidin (UniSZA ...
ScrapeStorm is developed by the former Google search technology team and based on artificial intelligence technology. ...
[1] , TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment presented by Biswas et al. ...
doi:10.1109/access.2021.3067844
fatcat:yyj22l2fezasjagwbfkfssscdy