• The Journal of Korean Association of Computer Education
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• v.11 no.1
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• pp.11-21
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• 2008

In advance of Knowledge Information Society, mentoring is becoming an efficient method for developing and managing human resources. There are several factors to improve the effect of mentoring. Among them, a matching mechanism that connects a mentee and a mentor is the most important in mentoring. In the existing e-mentoring systems, administrators rarely consider personal data. They match suitable mentors for mentees in a mandatory way, which reflects bad effects in the e-mentoring. In this paper, we propose new recommendation algorithms for matching by analyzing personal preferences for secondary school students to improve the effects of the mentoring. In addition, we compare our algorithms with the existing algorithms in terms of elaborateness, accordance, and diversity in order to prove the effectiveness of the proposed algorithms.

• Asia pacific journal of information systems
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• v.34 no.1
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• pp.1-25
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• 2024

Consumer demand for e-commerce services has skyrocketed due to the introduction of social distancing standards and lockdown measures that countries have taken to combat the pandemic. There has been a notable surge in the popularity of on-demand delivery services, with a significant influx of new users turning to the e-platform for assistance. This research paper tries to identify the enablers of E-commerce Utility and Service Quality and establish a connection using total interpretive structural modelling (TISM). Enablers are the building blocks for providing customers with an enhanced and more consistent service experience contributing to service quality. The enablers and the linkages thus established hold valuable insights for e-commerce marketers, aiding them in effectively reaching their customers, and achieving desired growth outcomes. The TISM- based model and the MICMAC analysis identified two barriers; website design and personalization as the decisive attributes of e-commerce service quality, possessing strong driving power and weak dependence. Furthermore, the factors of reliability, responsiveness, information, and ease of use form the linkage zone, indicating that any action taken on these factors would not only influence other factors but also have a reciprocal effect on them.

• 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.

• The Journal of the Korea Contents Association
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• v.2 no.1
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• pp.113-119
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• 2002

E-Biz. system must provide convenient and easy interface, efficient functions, and provides information and contents satisfying customers. To do this, many kinds of studies are being advanced actively about E-Biz. system using intelligent agent technology and efficient E-Biz. strategy. Also E-Biz. system score a lot of information and contents to get a efficient business activities and relationships between a company arid customers. To effectively adopt individual customer's preference and actively adapt change of business situation, we may consider individual user characteristics and emotion. This paper suggests E-Biz. system using intelligent agent technology based on user characteristics and emotion. This system can provide convenient user interface and improve customer royalty. In the results, it is found that proposed system is more efficient than existing systems about customer's preference.

• International Commerce and Information Review
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• v.3 no.1
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• pp.157-176
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• 2001

국내외 마케팅에 있어서 경쟁의 심화로 말미암아 새로운 고객의 획득에 따른 비용-효과보다 기존고객과의 관계유지를 위하여 고객의 평생가치를 높이도록 노력하는 것이 오히려 효과적인 경우가 많아졌다. 이러한 관계마케팅의 개념은 최근 마케팅을 포함한 기업경영 전반에 적용되는 고객관계관리(CRM)로 확장되고 있다. 또한 인터넷 기반의 e CRM이 고객행동의 분석도구를 거의 정확하고도 실시간으로 파악할 수 있게 함으로써 통합적 CRM의 아키텍쳐와 솔루션이 개발, 적용되고 있다. 통합 CRM에서의 고객은 B2B이든 B2C이든 간에 개별(개인) 고객을 가리키며, 개별 고객의 니즈와 요구를 적절하게 충족시킬 수 있도록 개인화 시스템을 구축하여 관리하는 것이 중요하다. 따라서 본 논문에서는 통합 CRM의 기본 틀과 시스템을 비롯하여 개인화 설계를 어떻게 할 것인가에 관한 사례 및 실증분석에 앞서 그 배경 지식을 정리하고자 이론적 탐구를 하였다.

• 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 Contents Association Conference
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• 2003.11a
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• pp.60-64
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• 2003

Individualization serverces to be persuited in most web sites are not one automated by system but collectivization services provided into several groups with information collected in initial register. Also, as most of the web sites provide individualization services according to environmental setting fitted by each individual, it is hard to offer to provide them with analyzing members by system itself. In this paper, as we store behavior characters of members on web surfing into member database and anlyze them automatically, system itself enables to provide individualization services.

• Journal of Digital Convergence
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• v.5 no.2
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• pp.59-70
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• 2007

Recently, rising of the convergence of technologies such as IT, GIS, GPS, and Sensors is developing the new information environment which enables man-to-man, man-to-object and object-to-object to exchange information anywhere and anytime. The Korean government has made great efforts to implement the virtual government with development of the next generation technologies continually and dynamically. These efforts for implementing e-government can be summarized by the citizen centered, integrated services, the customized personalization, the intellectual services, and the integration and cooperation between each offices for providing those services. Therefore, we wish to present the model of wide-area intelligent information systems which can provide services to form the future of this virtual government with GIS infrastructure in this study.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.331-339
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• 2004

The preferences of customers change over time. However, existing collaborative filtering (CF) systems are static, since they only incorporate information regarding whether a customer buys a product during a certain period and do not make use of the purchase sequences of customers. Therefore, the quality of the recommendations of the typical CF could be improved through the use of information on such sequences. In this paper, we propose a new methodology for enhancing the quality of CF recommendation that uses customer purchase sequences. The proposed methodology is applied to a large department store in Korea and compared to existing CF techniques. Various experiments using real-world data demonstrate that the proposed methodology provides higher quality recommendations than do typical CF techniques, with better performance, especially with regard to heavy users.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.1
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• pp.17-32
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• 2022

This study aimed to examine the effect of ad attributes on engagement, the mediating effect of engagement on the relationship between ad attributes and advertising effectiveness (attitudes toward ads, continuous intention to search, and e-WOM intention), and the differences in advertising effectiveness at different levels (low vs. high) of curiosity toward fashion video ads in the online context. For this purpose, a total of 408 responses were collected from consumers who were aged 20-40 years and had viewed fashion video ads via PC/mobile channels in the preceding six months. The results showed that three advertising attributes, namely informativeness, entertainment, and personalization, were significant predictors of engagement. Additionally, engagement had a significant mediating effect on the relationship between entertainment and ad effectiveness. Moreover, both informativeness and entertainment had a significant direct effect on the behavioral intention to search and engage in e-WOM. At the high-curiosity level, engagement had a significant influence on ad attitudes and e-WOM intention. In contrast, at the low-curiosity level, entertainment had a significant influence on e-WOM intention and continuous intention to search. These findings are meaningful in that they extend the advertising attitude model to fashion video ads in the online context.