• Journal of Information Technology Services
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• v.20 no.6
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• pp.1-16
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• 2021

The health functional food market continues to grow, and according to that trend, the subdivision sales of personalized health functional foods, which have been legally prohibited, will be operated as a special regulatory pilot project. Personalized health functional food recommendations have a variety of personalized indicators to consider, and it is believed that algorithmic methods will be needed to proceed in a customized manner considering all of them. This study aims to contribute to the development of the AI-based health functional food recommendation service by studying factors that affect the use of the AI-based health functional food recommendation service. This paper analyzed the intention of use for AI-based health functional food recommendation service based on the information system success model and Technology Acceptance Model. This study considered information quality factors, service quality factor, and system quality factor as independent variables influencing perceived usefulness, perceived ease of use and trust. For empirical analysis, 406 questionnaires were used and the collected data were performed using AMOS 22.0 and SPSS 22.0. Research has shown that the accuracy, timeliness, empathy and availability have a positive effect on usefulness. Understandability and availability has been shown to have a positive effect on ease of use. The accuracy, understandability, empathy and availibility has been shown to have a positive impact on Trust. Usefulness, ease of use and trust all have been shown to have a positive influence on intention of use.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.354-360
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• 2006

The purpose of this paper is to propose a securely personalized context-aware cooperative query that supports a multi-level data abstraction hierarchy and conceptual distance metric among data values, while considering privacy concerns around user context awareness. The conceptual distance expresses a semantic similarity among data values with a quantitative measure, and thus the conceptual distance enables query results to be ranked. To show the feasibility of the methodology proposed in this paper we have implemented a prototype system in the area of site search in a large-scale shopping mall.

• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1356-1366
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• 2007

Many personalized Services that provide users with adaptive information according to users' requirements and preferences have been researched and developed. However, existing approaches are difficult to share a user's information among heterogeneous services because these approaches manage users' preferences in a single system. In this paper, we propose a user preference sharing model based on the Semantic Web as a solution to resolve the problem. Our model enables user preferences to be described and shared over service-specific ontologies which are affected by the feature of each service. Our model is analyzed and evaluated with an implementation of the middleware that supports our model. Our approach has the advantage of providing more efficient personalized services than existing approaches because it can describe users' preferences centering around each service and share these information among heterogeneous personalized services.

• Journal of Genetic Medicine
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• v.5 no.2
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• pp.89-93
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• 2008

"Personalized medicine," the goal of which is to provide better clinical care by applying patient's own genomic information to their health care is a global challenge for the $21^{st}$ century "genomic era." This is especially true in Korea, where provisions for clinical genetic services are inadequate for the existing demand, let alone future demands. Genomics-based knowledge and tools make it possible to approach each patient as a unique biological individual, which has led to a paradigm-shift in medical practice, giving it more of a predictive focus as compared with current treatment oriented approach. With recent advancements in genomics, many genetic tests, such as susceptibility genetic tests, have been developed for both rare single gene diseases and more common multifactorial diseases. Indeed, genetic tests for presymtomatic individuals and genetic tests for drug response have become widely available, and personalized medicine will face the challenge of assisting patients who use such tests to make appropriate and wise use of genetic risk assessment. A major challenge of genomic medicine lies in understanding and communicating disease risk in order to facilitate and support patients and their families in making informed decisions. Establishment of a health care system with provisions for genetic counseling as an integral part of health care service, in addition to genomic literacy of health care providers, is vital to meet this growing challenge. Realization of the promise of personalized medicine in the era of genomics for improvement of health care is dependent on further development of next generation sequencing technology and affordable sequencing test costs. Also necessary will be policy development concerning the ethical, legal and social issues of genomic medicine and an educated and ready medical community with clinical practice guidelines for genetic counseling and genetic testing.

• Convergence Security Journal
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• v.15 no.5
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• pp.23-28
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• 2015

This study was carried out the exercise monitoring utilizing mobile device which is easily accessible and personalized exercise prescription based on it. For this, a variety of exercise monitoring and status of those were investigated and suggested the potential of personalized exercise prescription. If individual users send their body and vital informations using a mobile device, all informations are collected in u-Fitness center. After then exercise expert provide a customized prescription based on the collected information and feed data into database of u-Fitness center. System of U-Fitness center will provide the best personalized exercise prescription by automatically connecting to the content providers. In the future, a variety of mobile devices and services will work together and it can be evolved as an open platform that can be used for multiple services according to the needs of individual users on a single platform.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.67-75
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• 2020

The 'level of difficulty' is one of the major factors for learners when selecting learning contents. However, the criteria for the difficulty level is mostly defined by the contents providers. This approach does not support the personalized education which should consider the abilities and environments of various learners. In this research, the knowledge of the learners and contents were formalized and generalized to resolve the issue, and object models, including a metric for personalized difficulty level, were designed in order to be applied for experiments. And then, based on 100 contents for music education and 20 learners, we performed simulations with an implemented tool to validate our approach. The experimental results showed that our method can calculate the personalized difficulty levels considering the similarities between the knowledges from the learning state and the contents. Our approach can be effectively applied to the on-line learning management system which contains easy access to the learning state and contents data.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.187-196
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• 2021

The mobility handicapped are representative socially vulnerable people who account for a high percentage of our society. Due to the recent development of technology, personalized welfare technologies for the socially vulnerable are being studied, but it is relatively insufficient compared to the general people. In this study, we intend to implement a personalized restaurant recommendation system for the mobility handicapped. To this end, a hybrid recommendation system was implemented by combining the data of special transportation boarding and alighting history (7,153 cases) and information of Daegu Food restaurants (955 cases). In order to evaluate the effectiveness of the implemented recommendation system, we conducted performance comparisons with existing recommendation systems by prediction error rate and recommendation coverage. As a result of the analysis, the performance was higher than that of the existing recommendation system, and the possibility of a personalized restaurant recommendation system for the mobility handicapped was confirmed. In addition, we also confirmed the correlation in which similar restaurants are recommended in some types of the mobility handicapped. As a result of this study, it is judged that it will contribute to the use of restaurants with high satisfaction for the mobility handicapped, and the limitations of the study are also presented.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.4
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• pp.73-79
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• 2013

Recently, smart TVs have widely spread in our daily lives. However, it is difficult for users to find proper TV contents among a lot of TV and application contents because of inconvenience of input devices compared with those of smart phones or smart pads, so there are some problems with very low utilization of the smart functionalities of smart TVs. We suggest a personalized contents recommender system on smart TVs to resolve these problems and help for users to search appropriate contents easily and quickly in this research. We design and implement an intelligent system for personalized contents recommendation on the smart TVs based on multi-dimensional analysis considering user profiles and preferences, watching patterns of TV programs, and TV contents use statistics of TV users.

• Journal of Intelligence and Information Systems
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• v.11 no.3
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• pp.1-23
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• 2005

Personalized reminder systems have to identify the user's current needs dynamically and proactively based on the user's current context. However, need identification methodologies and their feasible architectures for personalized reminder systems have been so far rare. Hence, this paper aims to propose a proactive need awaring mechanism by applying agent, semantic web technologies and RFID-based context subsystem for a personalized reminder system which is one of the supporting systems for a robust ubiquitous service support environment. RescorlaWagner model is adopted as an underlying need awaring theory. We have created a prototype system called NAMA(Need Aware Multi-Agent)-RFID, to demonstrate the feasibility of the methodology and of the mobile settings framework that we propose in this paper. NAMA considers the context, user profile with preferences, and information about currently available services, to discover the user's current needs and then link the user to a set of services, which are implemented as web services. Moreover, to test if the proposed system works in terms of scalability, a simulation was performed and the results are described.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.66-73
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• 2007

Internet is a part of our common life and tremendous information is cumulated. In these trends, the personalization becomes a very important technology which could find exact information to present users. Previous personalized services use content based filtering which is able to recommend by analyzing the content and collaborative filtering which is able to recommend contents according to preference of users group. But, collaborative filtering needs the evaluation of some amount of data. Also, It cannot reflect all data of users because it recommends items based on data of some users who have similar inclination. Therefore, we need a new recommendation method which can recommend prefer items without preference data of users. In this paper, we proposed the apparel coordination system using personalized preference on the semantic web. This paper provides the results which this system can reduce the searching time and advance the customer satisfaction measurement according to user's feedback to system.