• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.367-371
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• 2005

The similarity measure is derived using fuzzy entropy and distance measure. By the elations of fuzzy entropy, distance measure, and similarity measure, we first obtain the fuzzy entropy. And with both fuzzy entropy and distance measure, similarity measure is obtained., We verify that the proposed measure become the similarity measure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.854-859
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• 2005

We construct the fuzzy entropy for measuring of uncertainty with the help of relation between distance measure and similarity measure. Proposed fuzzy entropy is constructed through distance measure. In this study, the distance measure is used Hamming distance measure. Also for the measure of similarity between fuzzy sets or crisp sets, we construct similarity measure through distance measure, and the proposed 려zzy entropies and similarity measures are proved.

• International journal of advanced smart convergence
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• v.5 no.2
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• pp.53-58
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• 2016

With the growing use of big data and data mining, it serves to understand how such techniques can be used to understand various relationships in the healthcare field. This study uses hierarchical methods of data analysis to explore similarities in hospitalization across several New York state counties. The study utilized methods of measuring crowding distance of data for age-specific hospitalization period. Crowding distance is defined as the longest distance, or least similarity, between urban cities. It is expected that the city of Clinton have the greatest distance, while Albany the other cities are closer because they are connected by the shortest distance to each step. Similarities were stronger across hospital stays categorized by age. Hierarchical clustering can be applied to predict the similarity of data across the 10 cities of hospitalization with the measurement of crowding distance. In order to enhance the performance of hierarchical clustering, comparison can be made across congestion distance when crowding distance is applied first through the application of converting text to an attribute vector. Measurements of similarity between two objects are dependent on the measurement method used in clustering but is distinguished from the similarity of the distance; where the smaller the distance value the more similar two things are to one other. By applying this specific technique, it is found that the distance between crowding is reduced consistently in relationship to similarity between the data increases to enhance the performance of the experiments through the application of special techniques. Furthermore, through the similarity by city hospitalization period, when the construction of hospital wards in cities, by referring to results of experiments, or predict possible will land to the extent of the size of the hospital facilities hospital stay is expected to be useful in efficiently managing the patient in a similar area.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.521-526
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• 2005

The fuzzy entropy is proposed for measuring of uncertainty with the help of relation between distance measure and similarity measure. The proposed fuzzy entropy is constructed through a distance measure. In this study, Hamming distance measure is employed for a distance measure. Also a similarity measure is constructed through a distance measure for the measure of similarity between fuzzy sets or crisp sets and the proposed fuzzy entropies and similarity measures are proved.

• The Journal of Information Systems
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• v.31 no.2
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• pp.89-110
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• 2022

Purpose To verify the factors that encourage consumers' favorable reaction toward virtual influencer, we proposed consumers' perception of subjective and objective similarity. The purpose of this study is to comprehensively investigate the impacts of consumers' perception toward virtual influencer on purchase intention through psychological distance and parasocial relationship. Design/methodology/approach This study was designed to examine the structural relationships among consumers' perceived external similarity, internal similarity, controllability, animacy toward virtual influencer, psychological distance, parasocial relationship and purchase intention. Findings The results are as follows. First, perceived external similarity, internal similarity, perceived controllability, and animacy had a positive impact on psychological distance. Second, psychological distance had a positive impact on parasocial relationship, whereas it had no significant impact on purchase intention. However, we found that the relation between psychological distance and purchase intention was mediated by parasocial relationship. Lastly, parasocial relationship had a positive impact on purchase intention. Based on these results, this study can propose the way to generate revenue to companies that consider advertising campaign using virtual influencer.

• 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 Pharmaceutical Investigation
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• v.30 no.2
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• pp.85-91
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• 2000

We have studied the dissolution kinetics of two fast releasing tablets in four media, and the similarity of dissolution profiles was compared using 3 methods. Two of the methods were introduced from statistical algorithm of distance methods, which are maximum distance and Mahalanobis distance. The dissolution kinetics were also analysed using FDA method for similarity evaluation, and the results were compared with those obtained using the distance methods.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.533-535
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• 2003

The Euclidean distance is sensitive to the absolute offsets of time sequences, so it is not a suitable similarity measure in terms of shape. In this paper. we propose an indexing scheme for efficient matching and retrieval of time sequences based on the minimum distance. The minimum distance can give a better estimation of similarity in shape between two time sequences. Our indexing scheme can match time sequences of similar shapes irrespective of their vortical positions and guarantees no false dismissals

• Journal of the Korea Convergence Society
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• v.4 no.3
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• pp.35-41
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• 2013

Grouping problem with similarities between DNA sequences are studied. The similaritymeasure and the distance measure showed the complementary characteristics. Distance measure can be obtained by complementing similarity measure, and vice versa. Similarity measure is derived and proved. Usefulness of the proposed similarity measure is applied to grouping problem of 25 cockroach DNA sequences. By calculation of DNA similarity, 25 cockroaches are clustered by four groups, and the results are compared with the previous neighbor-joining method.

• The Journal of the Acoustical Society of Korea
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• v.26 no.2E
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• pp.39-43
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• 2007

Music summarization refers to a technique which automatically extracts the most important and representative segments in music content. In this paper, we propose and evaluate a technique which provides the repeated part in music content as music summary. For extracting a repeated segment in music content, the proposed algorithm uses the weighted sum of similarity measures based on multi-level vector quantization for fixed-length summary or optimal-length summary. For similarity measures, count-based similarity measure and distance-based similarity measure are proposed. The number of the same codeword and the Mahalanobis distance of features which have same codeword at the same position in segments are used for count-based and distance-based similarity measure, respectively. Fixed-length music summary is evaluated by measuring the overlapping ratio between hand-made repeated parts and automatically generated ones. Optimal-length music summary is evaluated by calculating how much automatically generated music summary includes repeated parts of the music content. From experiments we observed that optimal-length summary could capture the repeated parts in music content more effectively in terms of summary length than fixed-length summary.