• Science of Emotion and Sensibility
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• v.9 no.spc3
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• pp.179-185
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• 2006

This study examines and compares various recommendation techniques which have been used successfully in other fields and seeks for opportunity to improve design personalization service more effectively. Throughout the literature study, several major recommendation techniques were identified, namely 'contents-based filtering', 'collaborative filtering', and 'demographic filtering'. In order for finding out relative advantages and disadvantages, a case study was carried out by applying different techniques. The result showed that in general, demographic filtering was evaluated least efficient among the techniques. Content-based filtering showed the best efficiency among them. Another significant finding was that the collaborative filtering had a better efficiency as the number of test subjects is increased. In conclusion, we suggest that design recommendation services can be improved by applying contents-based or collaborative filtering for better efficiency of recommendation. And, if the number of test subjects is large enough, it may be possible to remarkably improve the efficiency of design recommendation services by using collaborative filtering.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.192-197
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• 2001

A recommendation system tracks past actions of a group of users to make a recommendation to individual members of the group. The computer-mediated marketing and commerce have grown rapidly nowadays so the concerns about various recommendation procedures are increasing. We introduce a recommendation methodology by which e-commerce sites suggest new products of services to their customers. The suggested methodology is based on web log analysis, product taxonomy, and association rule mining. A product recommendation system is developed based on our suggested methodology and applied to a Korean internet shopping mall. The validity of our recommendation system is discussed with the analysis of a real internet shopping mall case.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11c
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• pp.1765-1768
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• 2002

최근 들어 웹사이트 개인화(Web Personalization)에 관한 연구가 활발히 진행되고 있다. 웹 개인화는 클러스터링과 같은 데이터 마이닝 기법을 이용하여 개개의 사용자에게 가장 흥미를 갖을만한 URLs의 집합을 예측하는 것이라 할 수 있다. 기존에는 웹 트랜잭션을 클러스터링 하기 위해서 사용자의 방문여부에 따라 트랜잭션을 비트벡터(bit vector)로 표현하였다. 하지만 이것은 웹 트랜잭션의 클러스터링에 있어서 사용자의 흥미를 배제하고 단순히 방문여부만을 반영하게 된다. 이에 본 논문에서는 사용자의 흥미도(Interestingness)를 반영할 수 있도록 보완된 웹 트랜잭션 모델을 제시하고 제안된 트랜잭션 모델을 적용한 유사도 비교방법을 제안한다. 그리고 성능평가를 통하여 제안한 방법이 기존 방법에 비해 클러스터링의 정확성을 높임을 보인다.

• The Journal of Information Technology and Database
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• v.8 no.2
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• pp.1-15
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• 2001

In trying to bring about online CRM(customer relationship management), companies have paid much attention to eCRM. The key of eCRM is a recommendation system, which is being used by E-commerce sites to find products to purchase. To maintain a constant flow of marketing information and feedback it is important to staying in touch with customers. In this respect, eCRM becomes a serious business tool for sales activities. In this article we present tee case of Kookmin Internet banking eCRM welch is one of the first examples of implementing eCRM in commercial web site in Korea. We examine how Kookmin Internet banking develops eCRM and how it provides customized services to customers. We also explore the role of eCRM in Internet banking and the level of personalization technology used in Kookmin eCRM case.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.416-425
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• 2003

Recommender systems are a personalized information filtering technology to help customers find the products they would like to purchase. Collaborative filtering (CF) has been known to be the most successful recommendation technology. However its widespread use in e-commerce has exposed two research issues, sparsity and scalability. In this paper, we propose several hybrid recommender procedures based on web usage mining, clustering techniques and collaborative filtering to address these issues. Experimental evaluation of suggested procedures on real e-commerce data shows interesting relation between characteristics of procedures and diverse situations.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.567-569
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• 2021

Due to the important role of avatars in computer-mediated communication (CMC), a growing number of CMC-based services now support avatar customization options. However, in many cases, customization and personalization options are limited to visual features. In this paper, we propose and describe a prototype for a vocal customization web application. Titled Voice Creator, the app is designed for both able-bodied and speech- or hearing-impaired users who seek to communicate anonymously using digital voice identities.

• Journal of Fashion Business
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• v.21 no.1
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• pp.134-147
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• 2017

The purpose of this study is to analyze fashion brands' contents and characteristics of the participation platform of users, to assess the types and strategies of mass customization(MC). Most fashion brands sell one professional content: Shoes brands were the most common, followed by bags, unisex wear, and menswear. In consumer's design selection elements, changes in color and materials were the most common. For the personalization service elements, monogram service was the most common. The results of MC types analysis were as follows, Customized Standardization was the most common, followed by Tailored Customization, Pure Customization, and Segmented Standardization. For the types according to changes in products and expression methods, Cosmetic was the most common. And the classification according to modulation, Modularizers were the most common. For Creativity, brands in the making stage were the most common. For Flexibility, although brands different methods, high flexibility by modularizing design elements of products and accomplishing various design through participation. The Ease of use for various expression was generally high, parallel to Flexibility. For Durability, because consumers could receive end products only when they participated in the assembly stage in the on-line purchase, their continuous participation was not possible, so they participated only once. The typical types and strategy of MC were analyzed. The Customized Standardization type was the most common in shoes, bag, and womenswear brands. It was the Cosmetic type which could change colors and materials, the Modularizers, and had high Flexibility and Ease of use and low Durability.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.37-45
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• 2015

With advancement in information technologies and a better mobile environment, the paradigm of service is shifting again from web portals to networked-applications based on individual application programs. Furthermore, as more investment is being made in R&D, the efforts to enhance R&D productivity are becoming important. In this paper, we designed a personalized service model for developing a tool to assist researchers in their R&D activities. To do this, we first compared services and tools in terms of information activities of researchers in R&D. In addition, we also analyzed changes of information environment such as open expansion of information and data, enhancement of personal information protection, popularization of social networking service, very big contents, advances in web platform technology in terms of personalization, and defined some directions of developing a personalized service. Subsequently we designed a personalized service model of research support tool in the views of functions, contents, operation, and defined personalized design goals and principles for implementing it as standard, participation, and open.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.2
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• pp.206-218
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• 2002

In this paper, we design and implement a system that presents a method for selecting and providing personalized services independently without unifying the existing system platform with shopping malls joined in the hub site. This system provides a mechanism for gathering information left behind by many clients visiting Web sites for analysis of customers property, vector model for selecting personalized services, and mechanism for providing them to customers who visited in a shopping mall joined to the hub site. In a position of shopping mall site, this kind of personalization system can provide target advertisement, point marketing, and point share service etc. without changing existing shopping mall's environment through wrapper web server. Hub site customers can get personalized services from many shopping mall sites with only once registration for the hub site.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.608-613
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• 2006

There are many e-showing mall because of revitalization of e-commerce system. It is necessary to recommending system of products that is for saving time and effort of customer. In this paper, we propose the system that is applying classification among data mining techniques to analysis of log data of customer. This log data contains access of user and purchasing of products. The proposed system operates in two phases. The first phase is composed of data filter module and association extraction module among web pages. The second phase is composed of personalization module and rule generation module. Customer can easily know the recommended sites because the proposed system can present rank of the recommended web pages to customer. As a result, the proposed system can efficiently do recommending of products to customer.