A New Similarity Measure based on and Its Application to Linguistic Approximation


The KIPS Transactions:PartB , Vol. 8, No. 5, pp. 463-468, Oct. 2001
10.3745/KIPSTB.2001.8.5.463,   PDF Download:

Abstract

We propose a new similarity measure based on relative membership function (RMF). In this paper, the RMF is suggested to represent the relativity between fuzzy subsets easily. Since the shape of the RMF is determined according to the values of its parameters, we can easily represent the relativity between fuzzy subsets by adjusting only the values of its parameters. Hence, we can easily reflect the relativity among individuals or cultural differences when we represent the subjectivity by using the fuzzy subsets. In this case, these parameters may be regarded as feature points for determining the structure of a fuzzy subset. In the sequel, the degree of similarity between fuzzy subsets can be quickly computed by using the parameters of the RMF. We use Euclidean distance to compute the degree of similarity between fuzzy subsets represented by the RMF. In the meantime, we present a new linguistic approximation method as an application area of the proposed similarity measure and show its numerical example.


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Cite this article
[IEEE Style]
D. Y. Choi, "A New Similarity Measure based on and Its Application to Linguistic Approximation," The KIPS Transactions:PartB , vol. 8, no. 5, pp. 463-468, 2001. DOI: 10.3745/KIPSTB.2001.8.5.463.

[ACM Style]
Dae Young Choi. 2001. A New Similarity Measure based on and Its Application to Linguistic Approximation. The KIPS Transactions:PartB , 8, 5, (2001), 463-468. DOI: 10.3745/KIPSTB.2001.8.5.463.