A New Similarity Measure of Interval-Valued Intuitionistic Fuzzy Sets and its Application in Commodity Recommendation

Peng Luo(1*), Yongli Li(2), Chong Wu(3)

(1) Harbin Institute of Technology, Harbin, China
(2) Harbin Institute of Technology, Harbin, China
(3) Harbin Institute of Technology, Harbin, China
(*) Corresponding author


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Abstract


Similarity measures are used to measure the similarity degree between fuzzy sets. As an important content in fuzzy mathematics, similarity measure has been used in various fields such as pattern recognitions, multi-criteria fuzzy decision making and medical diagnosis. However, in terms of the existing measure similarity measures, they don’t consider the hesitancy of the fuzzy sets. Accordingly we propose a new similarity measure and prove that it is much more reasonable comparing with the previous similarity measure in the examples. Besides, we also apply it into the commodity recommendation
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Keywords


Interval-Valued Intuitionistic Fuzzy Set; Similarity Measure; Fuzzy Set; Commodity Recommendation

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