• Knowledge Management Research
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• v.11 no.5
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• pp.25-36
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• 2010

It is widely known that KMS (Knowledge Management System) plays a role of facilitator that contributes to upgrading the organizational performance. Despite this widespread belief, actual operation of KMS has been stalled at the level of being used only for the plain knowledge administration, not reaching the level of utilizing KMS strategically. In this sense, this case study suggests three successful KMS operation strategies-personalization strategy, socialization strategy, and technological strategy. Cases adopted in this study include HIRA(Health Insurance Review & Assessment Service) and KORAIL (Korea Railroad) where KMS has been successfully utilized to improve their organizational innovation and performance as well. Through scrutinizing the two cases, it was concluded that the proposed three KMS operation strategies have potentials of being generally applied to other KMS operation cases.

• Journal of Integrative Natural Science
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• v.13 no.3
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• pp.97-104
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• 2020

This study suggests the emotion space modeling and emotion inference methods suitable for personalized services based on psychological and emotional models. For personalized emotion space modeling taking into account the subjective disposition based on the empirical assessment of the personal emotions felt by the personalization process of emotion space was used as a decision support tool, the Analytic Hierarchy Process. This confirmed that the special learning to perform personalized emotion space modeling without considering the subjective tendencies. In particular to check the possible reasoning based on fuzzy emotion space modeling and sensitivity for the quantification and vague human emotion to it based on the inherent human sensitivity.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.476-479
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• 2005

The information available on the Internet has become widely used, primarily due to the ability of Web based E-Commerce and M-Commerce Retrieval Engines to find useful information for users. However, present day Commerce Retrieval Engines are far from perfect because they return results based on simple user keyword matches without any regard for the concepts in which the user is interested. In this thesis, we design and evaluate a Recommender system for web context aware based information retrieval using user profiles. Also, we designed personalization framework in ubiquitous environment based both e-commerce and m-commerce and presented the interaction of user profile including User XQuery pattern in semantic web.

• Asia pacific journal of information systems
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• v.14 no.4
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• pp.147-162
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• 2004

A major difference between on-line services and off-line services is in the quality of the service they provide. On-line services lack of dynamic interface between customers and service providers. Traditional studies on personalizing web services do not consider the intimacy level of customers to web services. This study suggests a web personalizing method to satisfy customers in on-line using intimacy theory, cluster analysis, and data mining. The goal of this study is to support customers in web with more intimate service. It also offers improved services to customers by personalizing web services dynamically.

• Knowledge Management Research
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• v.4 no.2
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• pp.19-34
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• 2003

This paper analyzes 96 Korean companies to illustrate the relationship between the knowledge management strategies and task characteristics. Knowledge management strategies can be categorized as being codification- and personalization-oriented. Task characteristics are analyzed from the perspective of content-oriented, process-oriented, number of exceptions, and analyzability. These results illustrate how companies should align the knowledge management strategies with task characteristics. It is found that codification strategy is more likely to be associated with high content-oriented and high analyzability task, and personalization strategy is with high process-oriented task. The survey result confirms that managers should adjust knowledge management strategies in view of the characteristics of the task.

• The International Journal of Costume Culture
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• v.5 no.1
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• pp.14-25
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• 2002

The purpose of this study is to define mass customization in the apparel industry and to discover, the apparel industry's potential to deliver customized apparel products. Different from product-centered mass Production, mass customization is focusing on customers' unique needs. The goal of mass customization is for customers to find exactly what they want at a reasonable price. Using new technologies such as 3-D body scanning and digital printing, mass customization can give customers customfit and personalized garments. Mass customization can satisfy a customer in terms of personalization, fit and design. Adoption of mass customization will open new opportunities for the apparel manufacturer of the future. Mass customization is a strategy that apparel manufacturers should consider for their goals.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.04b
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• pp.1041-1044
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• 2001

현재 웹 상에서 이루어지는 교육은 개별 학습자의 학습 기대 수준에 따라 주문형(customization)과 맞춤형(personalization)교육이 요구되고 있으나 대부분 웹을 통한 교육이 획일적 커리큘럼에 따라 진행되고, 동일한 형태의 피드백을 제공하고 있어 학습자 개개인의 수준에 맞는 컨텐츠의 제공과 적절한 피드백이 이루어지지 못하고 있다. 따라서 학습 효과를 높이기 위해서는 학습자 수준에 맞는 차별화된 컨텐츠를 구성하여 제공하여야 한다. 본 연구에서는 수준별 학습, 맞춤형 교육 서비스를 제공하기 위한 컨텐츠 구성방법에 관하여 논의한다. 양질의 맞춤형 컨텐츠를 구성하기 위해 컨텐츠를 영역별로 분류하여 모듈화하고, 맞춤형 컨텐츠를 효율적으로 관리하여 학습자의 지식영역별 습득정도를 파악하고, 학습자의 수준에 맞게 융통성이 있으며 동적으로 컨텐츠를 재구성함으로써 학습자에게 가장 적절한 컨텐츠를 추출하여, 반복 학습을 통한 교육의 질적 제고를 기대한다.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.1-21
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• 2015

This paper aims to assess the feasibility of a new and less-focused type of online sociability (the watching network) as a useful information source for personalized recommendations. In this paper, we recommend scientific articles of interests by using the shared interests between target users and their watching connections. Our recommendations are based on one typical social bookmarking system, CiteULike. The watching network-based recommendations, which use a much smaller size of user data, produces suggestions that are as good as the conventional Collaborative Filtering technique. The results demonstrate that the watching network is a useful information source and a feasible foundation for information personalization. Furthermore, the watching network is substitutable for anonymous peers of the Collaborative Filtering recommendations. This study shows the expandability of social network-based recommendations to the new type of online social networks.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.430-460
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• 2004

This study presented a personalization system that adopted a methodology which is applicable for digital content recommendation and executed by the Internet service providers. The system made a recommendation to the users on the basis of their preferences, while most techniques for recommending digital content have focused on considering the similarity of content. In addition, it developed a method of evaluation to determine the priority of recommendations and adopted measures when selecting a set of recommendations. To experiment the feasibility and effectiveness of the presented methodology, a prototype system was developed and was applied to an English newspaper on the Internet.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.189-192
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• 2004

The present much information of internet has to exist for innumerable user so that couldn't satisfy there's a variety of demand. so they have a demerit that search unnecessary information. However Web service is different with other mass media because It is possible that enable Mass Customization for Personalization strategy. In The paper suggest reasoning system that detect user connection location by using indirect abstraction techniques a kind of Case-based reasoning techniques.