Similarity measure design on overlapped and non-overlapped data

Abstract

Similarity measure design on non-overlapped data was carried out and compared with the case of overlapped data. Unconsistant feature of similarity on overlapped data to non-overlapped data was provided by example. By the artificial data illustration, it was proved that the conventional similarity measure was not proper to calculate the similarity measure of the non-overlapped case. To overcome the unbalance problem, similarity measure on non-overlapped data was obtained by considering neighbor information. Hence, different approaches to design similarity measure were proposed and proved by consideration of neighbor information. With the example of artificial data, similarity measure calculation was carried out. Similarity measure extension to intuitionistic fuzzy sets (IFSs) containing uncertainty named hesitance was also followed.