• Information Systems Review
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• v.25 no.4
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• pp.67-87
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• 2023

Many online shopping sites now offer personalized recommendation systems to improve consumers' shopping experiences by lowering costs (time, cost, etc.), catering to consumers' tastes, and stimulating consumers' potential shopping needs. So far, domestic and foreign research on the personalized recommendation system has mainly focused on the field of computer science, which is advantageous for obtaining accurate personalized recommendation results for users but difficult to continuously track the users' psychological states or behavioral intentions. This study attempted to investigate the effect of the characteristics of the personalized recommendation system in the online shopping environment on consumer perception and purchase intention for consumers using the Stimulus-Organism-Response (S-O-R) model. The analysis results adopted all hypotheses on the effect of the quality of the personalized recommendation system and information quality on trust and perceived value. Through the empirical results of this study, the factors influencing consumers' use of personalized recommendation system can be identified. In order to increase more purchase, online shopping companies need to understand consumers' tastes and improve the quality of the personalized system by improving the recommendation algorithm thus to provide more information about products.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2B
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• pp.361-371
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• 2010

To vitalize the terrestrial DMB market, we introduce a personalized DMB(PDMB) service model based on metadata, especially DMB ECG XML standardized by TTA, under the convergence of broadcasting and telecommunications. Also we introduce the personalized DMB service system developed to validate the conformance of DMB ECG XML standard and the usefulness of DMB ECG service. The personalized DMB service system is described in details from the authoring stage to the consumption stage of the contents. The results of experimental tests for the personalized DMB service system are also introduced in this paper. We finally address the possibility of making successful personalized DMB services in mobile multimedia broadcasting market.

• Journal of Information Technology Services
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• v.7 no.4
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• pp.231-246
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• 2008

This paper suggests an e-learning system model, a goal-driven personalized e-learning system, which increase the effectiveness of learning. An e-learning system following this model makes the learner choose the learning goal. The learner's choice would lead learning. Therefore, the system enables a personalized adaptive learning, which will raise the effectiveness of learning. Moreover, this paper proposes a SCORM standard, which modifies SCORM 2004 that has been insufficient to implement the "goal driven personalized e-learning system." We add a data model representing the goal that motivates learning, and propose a standard for statistics on learning objects usage. We propose each standard for contents model and sequencing information model which are parts of "goal driven personalized e-learning system." We also propose that manifest file should be added for the standard for contents model, and the file which represents the information of hierarchical structure and general learning paths should be added for the standard for sequencing information model. As a result, the system could sequence and search learning objects. We proposed an e-learning system and modified SCORM standards by considering the many factors of adaptive learning. We expect that the system enables us to optimally design personalized e-learning system.

• Journal of Microbiology and Biotechnology
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• v.32 no.12
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• pp.1497-1505
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• 2022

Recently, the concept of personalized nutrition has been developed, which states that food components do not always lead to the same metabolic responses, but vary from person to person. Although this concept has been studied based on individual genetic backgrounds, researchers have recently explored its potential role in the gut microbiome. The gut microbiota physiologically communicates with humans by forming a bidirectional relationship with the micronutrients, macronutrients, and phytochemicals consumed by the host. Furthermore, the gut microbiota can vary from person to person and can be easily shifted by diet. Therefore, several recent studies have reported the application of personalized nutrition to intestinal microflora. This review provides an overview of the interaction of diet with the gut microbiome and the latest evidence in understanding the inter-individual differences in dietary responsiveness according to individual baseline gut microbiota and microbiome-associated dietary intervention in diseases. The diversity of the gut microbiota and the presence of specific microorganisms can be attributed to physiological differences following dietary intervention. The difference in individual responsiveness based on the gut microbiota has the potential to become an important research approach for personalized nutrition and health management, although further well-designed large-scale studies are warranted.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.383-386
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• 2001

In this paper, we propose a new personalized information service method using multiple regression analysis for Internet shopping malls. We then apply the proposed method to Internet bookstore, and compare personalized Internet bookstore providing personalized book information with ordinary Internet bookstore providing random book information. Experiment results show that the personalization of Internet bookstore increases satisfaction and purchasing intent of customers.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.16-18
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• 2001

사용자와 컴퓨터간의 자연스러운 상호작용을 위하여 Emotional 캐릭터 에이전트에 대한 연구가 지속되고 있다 어플리케이션에 Emotional 캐릭터 에이전트의 사용자인터페이스 적용은 사용자와 컴퓨터간의 자연스럽고 Personalized된 상호작용을 가능하게 한다. Personalized Emotional 캐릭터 에이전트에 대한 연구는 다음과 같다. 1) 사용자행위 정보를 이용한 캐릭터의 감정 생성연구 2) 블랙보드시스템을 이용한 감정추론 연구 3) 생성된 감정을 캐릭터의 행동표현으로 변화시키기 감정과 캐릭터 행동간의 연계 연구 4) Personalized Emotional 캐릭터 에이전트를 어플리케이션에 적용하는 연구

• The Mathematical Education
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• v.56 no.2
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• pp.161-175
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• 2017

The purpose of this study is to compare and analyze the impact on low-achievers in mathematics who studied mathematics using Blended e-learning and Personalized system of instruction after school. Blended e-learning is defined as the management of e-learning using the e-study run by the education office in local. Personalized system of instruction was proceeded as follows; (1) all students are given a syllabicated learning task and a study guide, (2) students study the material autonomously according to their own pace for a certain period of time, (3) the teacher strengthens the students' motivation through grading and feedback after students study a subject and solve the evaluation problem. The learning materials for Personalized system of instruction are re-edited the offline education contents provided by the blended e-learning to the level of students. The 118 $7^{th}$ grade students from the D middle school participated in this study. The results were verified by achievement tests before and after the study, as well as survey regarding their attitude toward mathematics. The results are as follows. First, Blended e-learning has more positive impacts than Personalized system of instruction in mathematics achievement. Second, there was no difference in mathematics achievement according to their self-directed learning between Blended e-learning and Personalized system of instruction. Third, both types utilizing Blended e-learning and Personalized system of instruction have positive effect on attitude toward mathematics, and there is not their difference between two methods of teaching and learning mathematics.

• Journal of the Korean Society for Library and Information Science
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• v.43 no.3
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• pp.163-180
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• 2009

In this paper, we describe a developmental system for establishing personal information tendency based on user queries. For each query, the system classified it based on the category information using a kNN classifier. As category information, we used DDC field which is already assigned to each record in the database. The system accumulates category information for all user queries and the user's personalized feature for the target database. We then developed a personalized retrieval system reflecting the personalized feature to produce search result. Our system re-ranks the result documents by adding more weights to the documents for which categories match with the user's personalized feature. By using user's tendency information, the ambiguity problem of the word could be solved. In this paper, we conducted experiments for personalized search and word sense disambiguation (WSD) on a collection of Korean journal articles of science and technology arena. Our experimental result and user's evaluation show that the performance of the personalized search system and WSD is proved to be useful for actual field services.

• Management & Information Systems Review
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• v.38 no.1
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• pp.23-41
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• 2019

Smart Factory is different from existing factory automation in that it aims to produce personalized products with minimum time and cost through ICT. However, previous researches, not from consumers but from product suppliers, have focused on technology trends and technology application methods. In order for Smart Factory to be successful, it must go beyond supplier-focus to meet the needs of consumers. In this study, we surveyed the purchase intention of the personalized product manufactured by smart factory. Influencing factors of purchase intention were drawn as consumers' need for uniqueness, innovativeness, need for touch, and privacy concern, based on previous research. As results of data analysis, it was confirmed that respondents were willing to purchase personalized products, and that consumers' need for uniqueness, innovativeness, and need for touch had a significant impact on purchase intention of personalized products. Our findings can be summarized as follows. First, Consumers' need for uniqueness was found to have positive effects(${\beta}=0.168$) on purchase intention of personalized products. The desire to differentiate themselves from others will be reflected in their personalized products. Therefore, consumers with a higher desire for uniqueness tend to be more willing to purchase personalized products. Second, consumer innovativeness was found to have positive effects(${\beta}=0.233$) on purchase intention of personalized products. Personalized shoes suggested in this study is a new type of personalized product that is manufactured by the latest information and communication technologies such as multi-function robots and 3D printing. Therefore, consumers seeking innovative new experiences are more willing to purchase personalized products. Third, need for touch was found to have positive effects(${\beta}=0.299$) on purchase intention of personalized products. In a smart factory environment, prosuming participation is given to consumers. If consumers participate in the product development process and reflect their requirements on the product, they are expected to increase their purchase intention by virtually satisfying the need for touch. Fourth, privacy concern was found to have no significantly related to purchase intention of personalized products. This is interpreted as a willingness to tolerate the risk of exposing personal information such as home address, telephone number, body size, and preference for consumers who feel highly useful in personalized products.

• ETRI Journal
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• v.36 no.5
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• pp.730-740
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• 2014

The rapid increase in the number of patients with chronic diseases is an important public healthcare issue in many countries, which accelerates many studies on a healthcare system that can, whenever and wherever, extract and process patient data. A patient with a chronic disease conducts self-management in an out-of-hospital environment, particularly in an at-home environment, so it is important to provide integrated and personalized healthcare services for effective care. To help provide effective care for chronic disease patients, we propose a service flow and a new cloud-based personalized healthcare system architecture supporting both at-home and at-hospital environments. The system considers the different characteristics of at-hospital and at-home environments, and it provides various chronic disease care services. A prototype implementation and a predicted cost model are provided to show the effectiveness of the system. The proposed personalized healthcare system can support cost-effective disease care in an at-hospital environment and personalized self-management of chronic disease in an at-home environment.