• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.23-30
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• 2010

With the advancement of information technology and increasing diversity in medical field, there are ongoing researches on ontology based intelligent medical system in Oriental medicine field. Intelligent diagnostic support system uses ontology to give a structure to complex medical knowledge and personal medical history so that we can make diagnosis more scientific, and provide better medical services. In this paper, we suggest an ontology that structuralize three knowledge types basic medical data, clinical trial data, and personal health information, which can be used as important information for individually tailored diagnosis. Especially in Oriental medicine diagnosis, both patient's symptoms of illness and physical constitution play a great role; it can lead to distinct diagnosis depending on their combination. Thus, it is much needed to have a diagnostic support system that uses personal health history and physical constitution along with basic medical data and clinical trial data in the field. In this paper, we implemented an Oriental medicine diagnostic support system that provides individualized diagnosis service to each patient by building an ontology on Oriental medicine focused on individual physical constitution and disease information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.579-586
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• 2021

This study examines the application of big data and tasks of tourism based on the case of Jeju Special Self-Governing Province, which used big data for regional tourism policy. Through the use of big data, it is possible to understand rapidly changing tourism trends and trends in the tourism industry in a timely and detailed manner. and also could be used to elaborate existing tourism statistics. In addition, beyond the level of big data analysis to understand tourism phenomena, its scope has expanded to provide a platform for providing real-time customized services. This was made possible by the cooperative governance of industry, government, and academia for data building, analysis, infrastructure, and utilization. As a task, the limitation of budget dependence and institutional problems such as the infrastructure for building personal-level data for personalized services, which are the ultimate goal of smart tourism, and the Personal Information Protection Act remain. In addition, expertise and technical limitations for data analysis and data linkage remain.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.513-520
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• 2021

Recently, research on edutech, which combines education and technology in the e-learning field called learning, education and training, has been actively conducted, but it is still insufficient to collect and utilize data tailored to individual learners based on learning activity data that can be automatically collected from digital devices. Therefore, this study attempts to detect questions in textbooks or problem papers using artificial intelligence computer vision technology that plays the same role as human eyes. The textbook or questionnaire item detection model proposed in this study can help collect, store, and analyze offline learning activity data in connection with intelligent education services without digital conversion of textbooks or questionnaires to help learners provide personalized learning services even in offline learning.

• Informatization Policy
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• v.30 no.3
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• pp.92-121
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• 2023

As music streaming services (MSS) involve various interactions with users during the music consumption process, it is important to understand the user experience and manage the service accordingly. This study developed a user experience model for MSS by theoretically linking the quality characteristics considered important by music service users with the structure of user experience. PLS analysis was then performed using survey data to test the model. As a result, functionality (search, browsing, and personalized recommendation), UI usability, content quality (currentness, sufficiency, relevance), and monetary cost were found to be key experience factors that determine the experience consequence, i.e., user satisfaction. In addition, in a supplementary analysis comparing domestic and global services, differences in user experience were found between the two groups in terms of functionality and content quality. The user experience model of MSS proposed in this study serves as a new foundation for theory-based research in this field and provides meaningful implications for the competitive landscape among music streaming service platforms and for their competitive strategies.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1285-1290
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• 2023

Although the environment in virtual space (hereinafter referred to as VR) has the problem of being difficult to access compared to existing PCs and smartphones, it has the advantage of being more realistic and providing endless experiences and functions compared to existing environments. In this VR environment, there is a need to develop technologies that help people handle tasks more conveniently in the virtual world by studying interfaces and interactions using ChatGPT, a recently popular AI technology. The ChatGPT interface and interaction in the VR environment are also studied to provide personalized services. Through this, users can choose the interface that suits them and the secretary interface can also provide customized services optimized for users. Accordingly, in this study, we design a convenient interaction method by linking the ChatGPT system in a VR environment and use it as a previous study for the development of an AI assistant.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.672-677
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• 2006

유비쿼터스 컴퓨팅 환경에서 상황 인지 서비스 제공을 위한 프레임워크들은 환경에 있는 응용 서비스들로 하여금 사용자 행동 패턴을 지속적으로 모니터링하며, 하나의 중앙집중식 서버에서 축적된 사용자 프로파일을 관리하도록 개발되어 왔다. 그러나, 전체 환경이 사용자 개개인의 서비스에 대한 요구 및 선호도를 파악하고 관리하는 일은 비효율적이다. 그리하여, 사용자 프로파일 관리 서버를 사용하지 않고 개인화된 서비스를 제공하기 위하여 휴대용 정보 단말기가 직접 사용자의 서비스에 대한 선호도를 인식하고 관리하는 사용자 프로파일 관리 프레임워크를 제안한다. 스마트 홈 환경의 이동형 사용자의 컨텍스트 인식을 위해서는 사용자 몸에 부착되어 있는 센서들이 사용자에 대한 정보를 휴대용 정보 단말기로 전달하며, 각 정보 단말기는 다양한 센서들로부터 획득한 정보와 정보단말기를 통해 제공되는 사용자의 직접적인 요구정보를 서비스 목적에 맞게 재해석하여 사용자 선호도에 맞는 서비스 내용을 제공하도록 하는 것이다. 제안된 프레임워크는 휴대용 정보 단말기를 통해 사용자와 환경과의 상호작용을 필요로 하는 유비쿼터스 기술이 활용 가능한 다양한 어플리케이션에 광범위하게 활용될 수 있다. 더 나아가, 사용자의 사적인 정보 보호를 보장하면서 개인화된 서비스 제공을 가능하게 할 수 있다.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.133-141
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• 2015

Mass multimedia contents are shared through various social media servies including social network service. As social network reveals user's current situation and interest, highly satisfactory personalized recommendation can be made when such features are applied to the recommendation system. In addition, classifying the music by emotion and using analyzed information about user's recent emotion or current situation by analyzing user's social network, it will be useful upon recommending music to the user. In this paper, we propose a music recommendation method that makes an emotion model to classify the music, classifies the music according to the emotion model, and extracts user's current emotional state represented on the social network to recommend music, and evaluates the validity of our method through experiments.

• Research in Community and Public Health Nursing
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• v.18 no.2
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• pp.301-309
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• 2007

Purpose: Based on the results of a survey on college freshmen's smoking this study examined the application of smoking cessation programs. Methods: The opinions of 89 smokers who were college freshmen were investigated and analyzed using a survey questionnaire. Results: Among the survey respondents, the largest percentage (47.2%) replied 'little satisfied' to the question on the with campus life. Of the participants, 57.3% considered that their health state was bad because of smoking. As to motives for smoking, 'curiosity' was most frequent. Smokers had more smoking friends than nonsmoking ones. The 82% of the smokers had experience in stopping smoking. Among smoking cessation methods, the self overcoming was most frequent(50.6%). During the survey, 28 smokers applied for the cessation program and they favored e-mails for information. E-mails were sent to them once in a week for 6 weeks and short messages were sent to their cell phone in order to encourage them to read the e-mails. Conclusions: To encourage and maintain smoking cessation, it is recommended to have a personalized or small group program. More researches are needed to execute the program and evaluate results. Colleges need to have an innovative approach on smoking prevention and cessation services.

• Journal of Korean Library and Information Science Society
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• v.49 no.1
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• pp.173-191
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• 2018

Over the past decade, the environment around libraries for the disabled has been greatly improved. Related legislation was established, facilities and facilities expanded, and the number of related collections and programs increased. In order to solve this problem, a survey of users' needs in accordance with the changing environment needs to be completed. In this study, we studied the existing research and analyzed the core needs of each type of disability employing user interviews and expert Delphi research. Users demanded quantitative and qualitative expansion of resources as well. Users needed personalized services and programs, convenience in using facility, accessibility of web and applications, and professional staff.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.157-172
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• 2013

There are many recommendation systems available to provide users with personalized services. Among them, the most frequently used in electronic commerce is 'collaborative filtering', which is a technique that provides a process of filtering customer information for the preparation of profiles and making recommendations of products that are expected to be preferred by other users, based on such information profiles. Collaborative filtering systems, however, have in their nature both technical issues such as sparsity, scalability, and transparency, as well as security issues in the collection of the information that becomes the basis for preparation of the profiles. In this paper, we suggest a movie recommendation system, based on the selection of optimal personal propensity variables and the utilization of a secure collaborating filtering system, in order to provide a solution to such sparsity and scalability issues. At the same time, we adopt 'push attack' principles to deal with the security vulnerability of collaborative filtering systems. Furthermore, we assess the system's applicability by using the open database MovieLens, and present a personal propensity framework for improvement in the performance of recommender systems. We successfully come up with a movie recommendation system through the selection of optimal personalization factors and the embodiment of a safe collaborative filtering system.