• The Journal of Society for e-Business Studies
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• v.6 no.1
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• pp.1-16
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• 2001

This paper describes a preliminary investigation of contracts with a view towards automating the process of contract match-making. A novel approach based on exploiting Standard Form Contracts(SFC) is described. The approach is shown to be implementable with current technology. A second approach based on Standard Contract Clauses(SCC) which overcomes some of the limitations of Standard Form Contracts, is briefly outlined. The flexibility offered by this approach however, is accompanied by a considerable increase in the complexity of contract match-making. Both Standard Form Contracts and Standard Contract Clauses based match-making point towards an exciting area of future research.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.177-192
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• 2012

This is a study of match-making systems that considers the mutual satisfaction of matching partners. Recently, recommendation systems have been applied to people recommendation, such as recommending new friends, employees, or dating partners. One of the prominent domain areas is match-making systems that recommend suitable dating partners to customers. A match-making system, however, is different from a product recommender system. First, a match-making system needs to satisfy the recommended partners as well as the customer, whereas a product recommender system only needs to satisfy the customer. Second, match-making systems need to include as many participants in a matching pool as possible for their recommendation results, even with unpopular customers. In other words, recommendations should not be focused only on a limited number of popular people; unpopular people should also be listed on someone else's matching results. In product recommender systems, it is acceptable to recommend the same popular items to many customers, since these items can easily be additionally supplied. However, in match-making systems, there are only a few popular people, and they may become overburdened with too many recommendations. Also, a successful match could cause a customer to drop out of the matching pool. Thus, match-making systems should provide recommendation services equally to all customers without favoring popular customers. The suggested match-making system, called Mutually Beneficial Matching (MBM), considers the reciprocal satisfaction of both the customer and the matched partner and also considers the number of customers who are excluded in the matching. A brief outline of the MBM method is as follows: First, it collects a customer's profile information, his/her preferable dating partner's profile information and the weights that he/she considers important when selecting dating partners. Then, it calculates the preference score of a customer to certain potential dating partners on the basis of the difference between them. The preference score of a certain partner to a customer is also calculated in this way. After that, the mutual preference score is produced by the two preference values calculated in the previous step using the proposed formula in this study. The proposed formula reflects the symmetry of preferences as well as their quantities. Finally, the MBM method recommends the top N partners having high mutual preference scores to a customer. The prototype of the suggested MBM system is implemented by JAVA and applied to an artificial dataset that is based on real survey results from major match-making companies in Korea. The results of the MBM method are compared with those of the other two conventional methods: Preference-Based Matching (PBM), which only considers a customer's preferences, and Arithmetic Mean-Based Matching (AMM), which considers the preferences of both the customer and the partner (although it does not reflect their symmetry in the matching results). We perform the comparisons in terms of criteria such as average preference of the matching partners, average symmetry, and the number of people who are excluded from the matching results by changing the number of recommendations to 5, 10, 15, 20, and 25. The results show that in many cases, the suggested MBM method produces average preferences and symmetries that are significantly higher than those of the PBM and AMM methods. Moreover, in every case, MBM produces a smaller pool of excluded people than those of the PBM method.

• The Journal of Korean Academy of Prosthodontics
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• v.16 no.1
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• pp.38-44
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• 1978

Color is an important factor in dental esthetics. Application of natural tooth color will not fail to produce pleasing results. But a standardized method of shade matching has not been adopted. If we are to overcome the color matching problem in dentistry, an understanding of the nature of color and light is essential. The purpose of this study was to compare the effects of different light sources and different background colors on the ability of observers to correctly match shades of artifical teeth. And observation was made to determine if the time spent in making a shade match was a factor in the correctness of the response. A test method was devised and 50 individuals made observations which were recorded and analyzed. $X^2$-test gave results indicating that the time factor had no effect on the response made. An analysis of variance showed the following effects significant at the five percent level; (1) light source (2) background color (3) subject. The following conclusions can be drawn from this study; (1) The time spent in making shade selection is not a factor in the correctness of the selections. (2) The light source used is an important factor in matching tooth shade; and there is no significant difference between the light sources in shade matching. (3) Under the conditions of this study, the greatest accuracy in shade matching was obtained on the brown background.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.781-784
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• 2000

전자중매 프로토콜(Match-making protocol)은 남녀간의 그룹미팅에서 커플을 구성하거나 특정 그룹 내에서 팀을 구성하기 위한 프로토콜이다. 본 연구에서는 두 사람이 서로 상대방을 선택했을 때에만 커플로 인정된다고 하는 규칙을 사용할 때 커플이 성립되었음을 확인하고 이를 증명하기 위한 안전하고 효율적인 프로토콜을 설계하였다. 이를 구현하기 위한 하부 프로토콜로서 두개의 이산대수 원소가 같은 지수값을 가지는지 여부를 증명하는 방법과 이를 이용하여 두개의 EIGamal 암호문이 제공되었을 때 복호화를 하지 않고도 평문 메시지가 일치하는지 여부를 확인하고 증명할 수 있는 프로토콜을 제시하고 이를 전자중매 프로토콜 설계에 이용하였다. 이러한 방법은 전자중매 프로토콜뿐만 아니라 실생활에서 요구되는 다양한 문제들을 해결하는 방법론으로 이용될 수 있을 것으로 예상된다.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.98-103
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• 2018

Globally, medical tourism draws attention as a national growth engine industry, and is actively expanding. Current medical tourism leans towards large hospitals making it difficult to attract new users. Users collect the information for medical tourism through various paths in order to receive medical consultations and customized tour services. To expand medical tourism to small and medium sized hospitals, it is necessary to have customized medical consultations, tours and interpreter services, which are the key elements of medical tourism. This paper suggests services that users can use to match medical consultations and find tours and interpreters they want at the same time. This paper suggests ways to provide integrated services based on the information experienced by users, combining the required items from the perspectives of each user, hospital and guide. To match the content provided by hospitals and guides with experience information from users systematically, this study suggests the convergence plan for a service model that can match the experience information between users and hospitals, between users and guides and between hospitals and guides systematically by operating the data in the universal container.

• The Research Journal of the Costume Culture
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• v.8 no.4
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• pp.537-548
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• 2000

This paper focuses on development of a fashion design education course that will foster the talent and aesthetic consciousness of fashion design student. The writer reached the content of the designing ideas to practical applications as the defined scope of fashion design education. For designing idea in practical application : matching ideas, contrasting ideas, formative combinations and revisionism were used. For design ideas, the ideas developed by 飯塚弘子, 万江入重子, 香川達子 were used in revision. To detail the content of design education, fashion magazines, portfolios, photographs and related fashion design educational materials were used. 1. Matching ideas : it proposes such identical expression into costume by making a research of developing material, application form and color extraction from design sources. 2. Contrasting ideas : it proposes such opposite expression into costume by making a research of opposite to image, form, position and purpose from some object. 3. Formative combinations : it proposes such new expression into costume by combining a detail of costume with the other object. 4. Revisionism : it proposes such modified expression into costume by making a research of deletion, change, addition and conversion in costume.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.214-222
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• 2021

Recently, the growth of e-commerce in Saudi Arabia has been exponential, bringing new remarkable challenges. A naive approach for product matching and categorization is needed to help consumers choose the right store to purchase a product. This paper presents a machine learning approach for product matching that combines deep learning techniques with standard artificial neural networks (ANNs). Existing methods focused on product matching, whereas our model compares products based on unstructured descriptions. We evaluated our electronics dataset model from three business-to-consumer (B2C) online stores by putting the match products collectively in one dataset. The performance evaluation based on k-mean classifier prediction from three real-world online stores demonstrates that the proposed algorithm outperforms the benchmarked approach by 80% on average F1-measure.

• Information Systems Review
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• v.8 no.2
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• pp.139-154
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• 2006

Recommender systems help users find their interesting items more easily or provide users with meaningful items based on their preferences. Collaborative filtering(CF) recommender systems, the most successful recommender system, use opinions of users to recommend for an active user who needs recommendation. That is, ratings which users have voted on items to indicate preference on them are the source for making recommendation. Although CF systems are designed only to use users' preferences as the source of recommendation, use of some available information is believed to increase both the performance and the accuracy of CF systems. In this paper, we propose a CF recommender system which utilizes both degree of match and demographic information(e.g., occupation, gender, age) to increase the performance and the accuracy. Since more and more information is accumulated in CF systems, it is important to reduce the data volume while maintaining the same or the higher level of accuracy. We used both degree of match and demographic information as criteria for reducing the data volume, thereby naturally enhancing the performance. It is shown that using degree of match improves the prediction accuracy too in CF systems and also that using some demographic information also results in better accuracy.

• Fashion & Textile Research Journal
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• v.24 no.4
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• pp.418-430
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• 2022

This study aims to analyze consumers' purchase decision-making process of buying avatar fashion items on the Metaverse platform. Drawing on the connection between the self-expression tendency of the MZ generation and that of avatars in the Metaverse, this study uses a qualitative research method to analyze how consumers express their self-image through the appearance of their avatars. Unlike previous studies on the clothing purchase decision-making process, this study shows that purchasing and consumption behavior involve the following six stages: recognizing desire, collecting information, evaluating alternatives, making purchases, evaluating the consumption, and post-purchase action-taking. In the first stage of the purchase decision-making process, consumers' desire arises with self-image expression and confirmation. In the second stage, consumers have a high tendency to shop in the best item category. In the alternative evaluation stage, consumers tend to seek items that match their highest standard while considering their personal preferences. In the fourth stage, when making actual purchases, unplanned purchase behavior often occurs along with an active practice of alternative evaluation. In the fifth stage, the evaluation of the consumption shows that consumers achieve satisfaction by applying a style to their avatars that they are unable to try in the real world. In the last stage, consumers often use their purchases to communicate their various styles with other online consumers. Therefore, we conclude that the online purchase decision-making process differs from the offline process as it is divided into six stages.

• Proceedings of the Costume Culture Conference
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• 2005.10a
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• pp.48-54
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• 2005

In order to mass-customize clothes, it is essential to take into account individual body shape using computerized 3D body models. This paper describes the development of an interactive body model that can be altered to match individual body perimeter, postures and depth for the purpose of computerized pattern making. Construction of the body model requires the extraction of necessary points, adjustment of coordinate points, linking of points by spline curves, control of section lengths and selectability of various hip types. Front to back depth of the model is adjusted by scaling ratio. We had a great result for controlling perimeter, posture and depth of body shapes. The results support the adaptability and potential usefulness of the posture and depth adjustable body model.