• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.10-16
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• 2015

In this study, we suggest a method to predict probability distribution of a new customer's degree of loyalty using C-CRF that reflects the RFM score and similarity to the neighbors of the customer. An RFM score prediction model is introduced to construct the first feature function of C-CRF. Integrating demographical similarity, purchasing characteristic similarity and purchase history similarity, we make a unified similarity variable to configure the second feature function of C-CRF. Then parameters of each feature function are estimated and we train our C-CRF model by training data set and suggest a probabilistic distribution to estimate a new customer's degree of loyalty. An example is provided to illustrate our model.

• The Journal of the Acoustical Society of Korea
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• v.3 no.1
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• pp.16-24
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• 1984

The objective data and subjective data correlated in order to rate sound quality of loudspeaker system and these data were analyzed by the Factor Analysis and Multi-Dimensioinal Scaling. The dimensions yielded Factor Analysis were interpreted as "Contrast", "Metallic", "Rich", "Present" and their relation to physical variables were explored by studying the positions of loudspeaker systems in the respective dimension. When the subjective similarity degree of loudspeaker systems was compared with the objective similarity degree of loudspeaker systems by Multi-Dimensional Scaling, the similarity degree of sound pressure response in the listening room closely coincided with the subjective similarity degree regardless of sound source. This result implies the necessity of measurements taken not only in an anechoic room but also in a listening room in order to rate sound quality of loudspeaker systems.

• The Mathematical Education
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• v.39 no.2
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• pp.167-177
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• 2000

In this thesis we concerned with the degree of similarity in pairs of scores having a common mean and variance could express similarity in terms of the absolute difference between the standardized scores. We particulary discussed the distribution of absolute differences between pairs of T scores among many standardized scores and demonstrated the procedures for calculating the lower limit of Med(│d│) values i. e. the maximum possible similarity with medians and correlation coefficients of the equivalent form tests by using the folded normal distribution, although other researchers expressed the degree of similarity using only the standard normal distribution. We also described many cases how to use those techniques and to apply effectively them in real evaluation fields.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.366-369
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• 2007

In this paper we derived fuzzy entropy that is based on similarity measure. Similarity measure represents the degree of similarity between two informations, those informations characteristics are not important. First we construct similarity measure between two informations, and derived entropy functions with obtained similarity measure. Obtained entropy is verified with proof. With the help of one-to-one similarity is also obtained through distance measure, this similarity measure is also proved in our paper.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.184-200
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• 2020

Similarity searching is a basic issue in information processing because of the large size of formal contexts and their complicated derivation operators. Recently, some researchers have focused on knowledge reduction methods by using granular computing. In this process, suitable information granules are vital to characterizing the quantities of attributes and objects. To address this problem, a novel approach to obtain an entropy-weighted concept lattice with inclusion degree and similarity distance (ECLisd) has been proposed. The approach aims to compute the combined weights by merging the inclusion degree and entropy degree between two concepts. In addition, another method is utilized to measure the hierarchical distance by considering the different degrees of importance of each attribute. Finally, the rationality of the ECLisd is validated via a comparative analysis.

• MALSORI
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• no.63
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• pp.47-66
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• 2007

This study aims at exploring the degree of phonetic similarity between Korean and Japanese vowels in terms of acoustic features by performing the speech production test on Korean speakers and Japanese speakers. For this purpose, the speech of 16 Japanese speakers for Japanese speech data, and the speech of 16 Korean speakers for Korean speech data were utilized. The findings in assessing the degree of the similarity of the 7 nearest equivalents of the Korean and Japanese vowels are as follows: First, Korean /i/ and /e/ turned out to display no significant differences in terms of F1 and F2 with their counterparts, Japanese /i/ and /e/, and the distribution of F1 and F2 of Korean /i/ and /e/ in the distributional map completely overlapped with Japanese /i/ and /e/. Accordingly, Korean /i/ and /e/ were believed to be "identical." Second, Korean /a/, /o/, and /i/ displayed a significant difference in either F1 or F2, but showed a great similarity in distribution of F1 and F2 with Japanese /a/, /o/, and /m/ respectively. Korean /a/ /o/, and /i/, therefore, were categorized as very similar to Japanese vowels. Third, Korean /u/, which has the counterpart /m/ in Japanese, showed a significant difference in both F1 and F2, and only half of the distribution overlapped. Thus, Korean /u/ was analyzed as being a moderately similar vowel to Japanese vowels. Fourth, Korean /${\wedge}$/ did not have a close counterpart in Japanese, and was classified as "the least similar vowel."

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.1
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• pp.76-81
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• 1999

The degree of relative similarity between 2D patterns is obtained using Open-Ball Scheme. Open-Ball Scheme employs a method of transforming the geometrical information on 3D objects or 2D patterns into the features to measure the relative similarity for object(patten) recognition, with invariance on scale, rotation, and translation. The feature of an object is used to obtain the relative similarity and mapped into [0, 1] the interval of real line. For decades, Moment-Invariant Method has been used as one of the excellent methods for pattern classification and object recognition. Open-Ball Scheme uses the geometrical structure of patterns while Moment Invariant Method uses the statistical characteristics. Open-Ball Scheme is compared to Moment Invariant Method with respect to the way that it interprets two-dimensional patten classification, especially the paradigms are compared by the degree of closeness to human's intuitive understanding. Finally the effectiveness of the proposed Open-Ball Scheme is illustrated through simulations.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.37-44
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• 2020

As the information society develops, various cases of copyright infringement have occurred. In many disputes between companies, software similarity appraisal is dominated. This thesis is a study on the method of calculating the similarity of the standards subject to appraisal. In other words, it is a study to calculate the amount of revision and addition of the specification to be assessed. The analysis method compares the table of contents of both specifications and finds the same or similar part. The similarity weight is determined according to the degree of similarity. Weights identify and assign the degree of similarity between the expert's expertise and the specification. If it is completely newly added, the similarity weight is 1, if it is partially modified, the similarity weight is 0.4, and if it is almost the same as before, it is calculated by giving a weight of 0.05. Through this paper, it was found that the result of calculating the similarity to the specification is 21.2 pages.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.603-608
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• 2009

In this paper, a similarity measure between interval-valued vague sets is proposed. In the interval-valued vague sets representation, the upper bound and the lower bound of a vague set are represented as intervals of interval-valued fuzzy set respectively. Proposed method combines the concept of geometric distance and the center-of-gravity point of interval-valued vague set to evaluate the degree of similarity between interval-valued vague sets. We also prove three properties of the proposed similarity measure. It provides a useful way to measure the degree of similarity between interval-valued vague sets.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.257-261
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• 2008

In this Paper we derived fuzzy entropy that is based on similarity measure. Similarity measure represents the degree of similarity between two informations, those informations characteristics are not important. First we construct similarity measure between two informations, and derived entropy functions with obtained similarity measure. Obtained entropy is verified with proof. With the help of one-to-one similarity is also obtained through distance measure, this similarity measure is also proved in our paper.