• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.154-159
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• 2006

본 논문은 웹 서버에 의해 자동으로 수집되는 로그 파일로부터 고객 가치 판단 기준을 고객의 행동 기반에 두고 군집화 기법을 이용하여 고객을 세분화하고 세분화 결과에 의사결정나무를 적용함으로써 고객을 분류하는 통합 모형을 제안하였다. 또한, 분류된 고객들의 주 서비스 활용 패턴을 분석하기 위하여 연관규칙기법을 적용하여 고객의 과학기술정보 활용의 연관성을 분석함으로써, 과학정보포털 서비스를 제공하는 사이트 이용자의 분류군에 해당하는 정보와 인터페이스를 제공하는 새로운 방법에 대하여 연구하였다. 고객 관리 측면에서 본 논문은 정보 서비스를 제공하는 웹 사이트의 기존고객을 분류하여 패턴을 분석함으로써 고객 위주의 사이트 운영정책과 동적 인터페이스를 제공하기 위한 웹사이트 활용 방안을 제시하였다. 또한, 고객의 지속적인 관리라 각 고객 분류군별에 안는 서비스를 제공하고 고객의 관리에도 기여할 수 있을 것이다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.482-486
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• 2006

1990년대 말부터 전세계적으로 이동통신 사용자의 수는 급증하였고, 2000년대에 들어서면서부터는 모바일 인터넷 사용자 수도 점차적으로 증가하고 있는 추세이다. 그러나 오프라인이나 기존e-commerce에서의 서비스 품질 측정에 대한 연구는 활발하게 이루어진 반면, 모바일 상거래에 관한 연구는 미미한 실정이다. 본 연구는 모바일 상거래에 대한 고객만족도에 영향을 미치는 요인을 찾아내고자 하는데 그 목적이 있다. 이를 위해, 모바일 상거래의 특징을 살펴봄으로써 모바일 상거래에서 고객 만족도에 영향을 미치는 요인들을 추출하고 체계적인 프레임워크를 제시하고자 한다. 또한 본 연구에서는 모바일 상거래 중 디지털 컨텐츠 다운로드 서비스의 실사용자들을 대상으로 설문조사를 실시하였으며 이를 토대로 Rasch 모형을 적용하여 고객군을 분류하고 요인별 중요도를 파악하며 고객만족에 대한 확률적 예측을 실행하였다.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.83-99
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• 2007

Nowadays, the advancement of digital information technology resulting in the increased interest of the management and the use of information has given stimulus to the research on the use and management of information. In this paper, we propose an integrated data mining model that can provide the necessary information and interface to users of scientific information portal service according to their respective classification groups. The integrated model classifies users from log files automatically collected by the web server based on users' behavioral patterns. By classifying the existing users of the web site, which provides information service, and analyzing their patterns, we proposed a web site utilization methodology that provides dynamic interface and user oriented site operating policy. In addition, we believe that our research can provide continuous web site user support, as well as provide information service according to user classification groups.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.771-774
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• 2012

세계적으로 온라인 평판 분석 서비스의 개발 및 SNS 이슈 분석과 영향도 평가 등의 서비스 이용추세가 증가하고 있다. 현재 SNS나 소셜미디어등 온라인을 통해 고객들의 서비스에 대한 정성적인 평가 및 요구사항이 실시간으로 표현되고 있으며, 서비스에 대한 부정적인 여론이 확산되기 전에 능동적으로 대응할 수 있는 시스템의 필요성이 기업들에게 시급히 요구되고 있다. 이러한 시스템 개발을 위해서 선행되어야 할 기술개발 요건으로 B2C 산업의 특성에 기반한 다양한 분석 주제를 설정하고, 이에 맞는 다양한 동일 산업군에 대한 시스템 적용을 위한 분류 표준화가 필수이다. 본 연구에서는 이를 수행하기 위해서 대표 산업군을 선정하여 기존 업무 분류 체계를 기반으로 한 온라인상의 고객 피드백 분류 및 표준화 수립에 대한 방법을 제안한다.

• 한국데이터정보과학회:학술대회논문집
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• 2001.10a
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• pp.12-12
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• 2001

정보기술을 바탕으로 전자상거래의 규모는 빠르게 늘어가고 있다. 본 연구에서는 종합쇼핑몰의 성격을 띠는 사이버 쇼핑몰의 고객과 구매 고객의 특성 등을 살펴보고 의사결정나무를 이용한 이탈고객의 분류, 쇼핑몰에 등록된 상품군과 인구특성적인 변수들간의 대응분석을 실시하여 쇼핑몰에 대한 인식을 제고한다.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.2
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• pp.259-266
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• 2017

The purpose of this study was to improve satisfaction of university dormitory foodservice customers by analyzing the correlation between foodservice satisfaction and customer loyalty. The questionnaire was distributed to 510 students residing in a dormitory of a University located in Gyengsangbuk-do from 1st to 8th December, 2015. The average customer satisfaction score was 3.19/5.00. The category with the highest score was sanitation, followed by environment, food, reactivity, and menu. Male students showed significantly higher foodservice satisfaction score than females in terms of reactivity (P<0.01) category. Students living in the dormitory for over 2 years were significantly less satisfied with the dormitory foodservice in terms of menu (P<0.05) and reactivity (P<0.001) categories. The average customer loyalty score was 2.73/5.00. Scores for revisit intention, words-of-mouth intention, and intent not to switch were 2.80, 2.73, and 2.65, respectively. Revisit intention and words-of-mouth intention showed a significant (P<0.001) positive correlation with food, environment, menu, sanitation, and reactivity. Non-switching intention showed a significant (P<0.001) positive correlation with food, menu, and reactivity. After classifying customers into four groups according to customer satisfaction and loyalty, a comparison was carried out to determine satisfaction and loyalty by each customer stratum. In the "loyalist" group, satisfaction with sanitation and the advertise intention by revisit and words-of-mouth were significantly higher than in the other groups (P<0.001). In "defector" group, satisfaction with menu (P<0.001) and advertise intention by words-of-mouth (P<0.01) were significantly lower than in the other groups.

• Information Systems Review
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• v.7 no.2
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• pp.23-40
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• 2005

Discovering customers' behavioral patterns from large data set and providing them with corresponding services or products are critical components in managing a current business. However, the diversity of customer needs coupled with the limited resources suggests that companies should make more efforts on understanding and managing specific groups of customers, not the whole customers. The key issue of this paper is based on the fact that the behavioral patterns extracted from the specific groups of customers shall be different from those from the whole customers. This paper proposes the idea of pre-segmentation before developing customer classification models. We collected three customers' demographic and transactional data sets from a credit card, a tele-communication, and an insurance company in Korea, and then segmented customers by major variables. Different churn prediction models were developed from each segments and the whole data set, respectively, using the decision tree induction approach, and compared in terms of the hit ratio and the simplicity of generated rules.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.376-379
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• 2008

People are experiencing severe navigation problems in mobile site Relatively limited research, however, has been conducted on mobile site navigation compared to web site navigation. This research aims to identify efficient mobile site navigation aids for timely preferred contents. It proposed timely menu system based on statistic data, and evaluates its efficiency through commercial beta test. We conducted a beta test in the fourth quarter of the year 2007. The total number of user is 12,000. The average number of PV (page view) by the experimental group was increased to 10% more than control group. Our results indicate that timely menu system helps people navigate mobile menu system more effectively.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.207-218
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• 2020

Recently, due to the increase of online reviews and the development of analysis technology, the interest and demand for online review analysis continues to increase. However, previous studies have not considered the emotions contained in each vocabulary may differ from one reviewer to another. Therefore, this study first classifies the customer group according to the customer's grade, and presents the result of analyzing the difference by performing review analysis for each customer group. We found that the price factor had a significant influence on the evaluation of products for customers with high ratings. On the contrary, in the case of low-grade customers, the degree of correspondence between the contents introduced in the mall and the actual product significantly influenced the evaluation of the product. We expect that the proposed methodology can be effectively used to establish differentiated marketing strategies by identifying factors that affect product evaluation by customer group.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.145-153
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• 2023

This study emphasizes the essential need in the military for effective measurement and monitoring of soldiers' physical fitness, health, and exercise capabilities to enhance both their overall fitness and combat effectiveness. The effective assessment of physical fitness is considered a core element of management, aligning with principles of modern management. Particularly, preparing soldiers with robust physical fitness is deemed crucial for adapting to dynamic changes on the battlefield. In this research, the RFM (Recency, Frequency, Monetary) customer analysis and clustering methods, validated in e-commerce, are introduced as a basis for applying an AI-driven customer analysis approach to assess military personnel fitness. To achieve this, the study explores the incorporation of the RSC (Reveal, Sustainable, Control) analysis model. This model aims to effectively categorize and monitor military personnel fitness. The application of the RFM technique in the RSC analysis model quantifies and models military fitness, fostering continuous improvement and seeking strategies to enhance the effectiveness of fitness management. Through these methods, the study develops an AI customer analysis technique applied to the RSC clustering analysis method for improving and sustaining military personnel fitness.