Aggregation operators in Hesitant Fuzzy Set for Decision Making 
Roopa Chandrika R1, Gowri Ganesh N.S2, Mummoorthy A3, Gayathri M4
1Roopa Chandrika R*, Computer Science, Malla Reddy College of Engineering and Technology, Hyderabad, Telangana, India.
2Gowri Ganesh N.S, Computer Science, Malla Reddy College of Engineering and Technology, Hyderabad, Telangana, India.
3Mummoorthy A, Computer Science, Malla Reddy College of Engineering and Technology, Hyderabad, Telangana, India.
4Gayathri A, Computer Science, Malla Reddy College of Engineering and Technology, Hyderabad, Telangana, India.
Manuscript received on October 04, 2021. | Revised Manuscript received on October 18, 2021. | Manuscript published on November 30, 2021. | PP: 101-105 | Volume-10 Issue-4, November 2021. | Retrieval Number: 100.1/ijrte.D65861110421| DOI: 10.35940/ijrte.D6586.1110421
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Uncertainty is prevalent in a wide range of real-world issues. The fuzzy sets, vague sets or intuitionistic fuzzy sets are widely used in recent years for decision making and various analysis where uncertainty is predominant. An extension of fuzzy sets is Hesitant Fuzzy Sets, which deals with ambiguous situations that arise when determining an element’s membership degree in a set. Researchers have defined various ideas, extensions, aggregation operators, and measurements to deal with reluctant information as a result of this new approach. Machine leaning algorithms are also exploiting hesitant fuzzy sets for better decision making.
Keywords: Aggregation operators, hesitant reviews, hesitant fuzzy sets, sentiment analysis