• Journal of Information Technology and Architecture
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• v.9 no.1
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• pp.57-66
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• 2012

Recently, with a rapidly growing of the mobile content market, a variety of mobile-based applications are being launched. But mobile devices, compared to the average computer, take a lot of effort and time to get the final contents you want to use due to the restrictions such as screen size and input methods. To solve this inconvenience, a recommender system is required, which provides customized information that users prefer by filtering and forecasting the information.In this study, an tailored multi-information recommendation system utilizing a Personalized information recommendation system on smartphone is proposed. Filtering of information is to predict and recommend the information the individual would prefer to by using the user-based collaborative filtering. At this time, the degree of similarity used for the user-based collaborative filtering process is Euclidean distance method using the Pearson's correlation coefficient as weight value.As a real applying case to evaluate the performance of the recommender system, the scenarios showing the usefulness of recommendation service for the actual restaurant is shown. Through the comparison experiment the augmented reality based multi-recommendation services to the existing single recommendation service, the usefulness of the recommendation services in this study is verified.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.117-124
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• 2021

In this paper, we propose CANVAS (Creative ANalytics enVironment And System), an analytics system of the National Research Data Platform (DataON). CANVAS is a personalized analytics cloud service for researchers who need computing resources and tools for research data analysis. CANVAS is designed in consideration of scalability based on micro-services architecture and was built on top of open-source software such as eGovernment Standard framework (Spring framework), Kubernetes, and JupyterLab. The built system provides personalized analytics environments to multiple users, enabling high-speed and large-capacity analysis by utilizing high-performance cloud infrastructure (CPU/GPU). More specifically, modeling and processing data is possible in JupyterLab or GUI workflow environment. Since CANVAS shares data with DataON, the research data registered by users or downloaded data can be directly processed in the CANVAS. As a result, CANVAS enhances the convenience of data analysis for users in DataON and contributes to the sharing and utilization of research data.

• CRM연구
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• v.4 no.1
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• pp.55-68
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• 2011

Recently with the development of Web services by utilizing a variety of web content, the studies on user experience and personalization based on web usage has attracted much attention. Majority of personalized analysis are have been carried out based on existing data, primarily using the database and statistical models. These approaches are difficult to reflect in a timely mannerm, and are limited to reflect the true behavioral characteristics because the data itself was just a result of customers' behaviors. However, recent studies and commercial products on web analytics try to track and analyze all of the actions from landing to exit to provide personalized service. In this study, by analyzing the customer's click-stream behaviors, we define U-Score(Usage Score), P-Score (Preference Score), M-Score(Mania Score) to indicate variety of customer preferences. With the devised three indicators, we can identify the customer's preferences more precisely, provide in-depth customer reports and customer relationship management, and utilize personalized recommender services.

• Journal of KIISE:Software and Applications
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• v.35 no.8
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• pp.522-528
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• 2008

Topic map typically provide information to user through the selection of topics, that is using only topic, association, occurrence on the first topicmap which is made by domain expert without regard to individual interests or context, for the purpose of supplementation for the weakness which is providing personalized topic map information, personalization has been studied for supporting user preference through preseting of customize, filtering, scope, etc in topic map. Nevertheless, personalization in current topicmap is not enough to user so far. In this paper, we propose a design of PTRS(personalized topicmap ranking system) & algorithm, using both user profile(click through data) and basic element of topic map(topic, association) on knowledge layer in specific domain topicmap, therefore User has strong point that is improvement of personal facilities to user through representation of ranked topicmap information in consideration of user preference using PTRS.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.88-97
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• 2013

Collaborative filtering(CF) for the personalized recommendation is a successful and popular method in recommender systems. But the mainly researched and implemented cases focus on dealing with independent items with explicit feedback by users. For the domain of TV program recommendation in VOD service platform, we need to consider the unique characteristic and constraints of the domain. In this paper, we studied on the way to convert the viewing history of each TV program episodes to the TV program preference by considering the series structure of TV program. The former is implicit for personalized preference, but the latter tells quite explicitly about the persistent preference. Collaborative filtering is done by the unit of series while data gathering and final recommendation is done by the unit of episodes. As a result, we modified CF to make it more suitable for the domain of TV program VOD recommendation. Our experimental study shows that it is more precise in performance, yet more compact in calculation compared to the plain CF approaches. It can be combined with other existing CF techniques as an algorithm module.

• The Journal of Korean Association of Computer Education
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• v.14 no.1
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• pp.91-109
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• 2011

This study describes the design and development of personalized e-Tutor to facilitate e-Learning. An e-Tutor was developed to provide personalized cognitive, emotional, and social learning supports automatically and integrated into an e-learning system. Fourteen learning supports selected in this study were consisted of eight cognitive, three emotional, and three social factors respectively. Participants were 202 adult learners in corporate training environments. The result indicated that e-Tutor was perceived useful in general. Amongst three, cognitive support was perceived as the most useful. Emotional and social supports of encouraging learners and facilitating interactions among learners were also reported useful to facilitate the desired learning outcomes.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.2
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• pp.179-186
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• 2014

Metabolomics is the study of changes in the metabolic status of an organism as a consequence of drug treatment, environmental influences, nutrition, lifestyle, genetic variations, toxic exposure, disease, stress, etc, through global or comprehensive identification and quantification of every single metabolite in a biological system. Since most chronic diseases have been demonstrated to be linked to nutrition, nutritional metabolomics has great potential for improving our understanding of the relationship between disease and nutritional status, nutrient, or diet intake by exploring the metabolic effects of a specific food challenge in a more global manner, and improving individual health. In particular, metabolite profiling of biofluids, such as blood, urine, or feces, together with multivariate statistical analysis provides an effective strategy for monitoring human metabolic responses to dietary interventions and lifestyle habits. Therefore, studies of nutritional metabolomics have recently been performed to investigate nutrition-related metabolic pathways and biomarkers, along with their interactions with several diseases, based on animal-, individual-, and population-based criteria with the goal of achieving personalized health care in the future. This article introduces analytical technologies and their application to determination of nutritional phenotypes and nutrition-related diseases in nutritional metabolomics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5771-5777
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• 2013

The need of continuous management for diseases came to the fore as a chronic disease has increased, however, research related to personalized food intake analysis are insufficient. In diabetes risk analysis model of this study, food preferences are calculated by Pearson correlation coefficient that is proven method to assess the similarity, and diabetes risk is computed as a Logistic regression that was used in prevalence studies. For the Significance evaluation of this model, it was verified through t-test at 0.05 level of 52 comparison subjects and 52 control subjects. Both groups were significantly independent (p=0.046 <0.05). This model is a new way to personalized health management, through the application to healthcare system based on web and mobile.

• Journal of Pharmacopuncture
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• v.23 no.2
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• pp.71-78
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• 2020

Objectives: This study was conducted to development of hazardous materials management standards for the decoction type of personalized herbal medicines (PHMs). Methods: This study was conducted in two stages. We searched documents about criteria to use words such as 'Herb', 'Herbal medicine', and 'Botanical Drug' and summarized the results. We organized the committee consisted of seven experts, and held two meetings to reach an agreement on hazardous management standards of the decoction type of PHMs. Results: The seven documents were presented in the literature review and six items related to hazardous management standards of decoction were identified. The second expert meeting brought that a total of six items, including heavy metal, pesticide residues, sulfur dioxide, benzopyrene, mycotoxin, and micro-organism limits, were selected for safety management of decoction type of PHMs. Also, the criteria and test methods for each standard were suggested for monitoring the decoction type of PHMs. Conclusion: The study suggested hazardous material management standards and criteria for the decoction types of PHMs. In the future, it would be necessary to conduct a pilot test to ensure the validity and credibility of the safety management standard and criteria. Furthermore, the government level safety management system should be introduced to verify the safety of decoction medicines.

• Journal of Korean Academy of Nursing
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• v.52 no.5
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• pp.535-549
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• 2022

Purpose: The study aimed to design and develop an automated personalized self-care (APSC) program for patients with type 2 diabetes mellitus. The secondary aim was to present a clinical protocol as a mixed-method research to test the program effects. Methods: The APSC program was developed in the order of analysis, design, implementation, and evaluation according to the software development life cycle, and was guided by the self-regulatory theory. The content validity, heuristics, and usability of the program were verified by experts and patients with type 2 diabetes mellitus. Results: The APSC program was developed based on goal setting, education, monitoring, and feedback components corresponding to the phases of forethought, performance/volitional control, and self-reflection of self-regulatory theory. Using the mobile application, the participants are able to learn from educational materials, monitor their health behaviors, receive weekly-automated personalized goals and feedback messages, and use an automated conversation system to solve the problems related to self-care. The ongoing two-year study utilizes a mixed method design, with 180 patients having type 2 diabetes mellitus randomized to receive either the intervention or usual care. The participants will be reviewed for self-care self-efficacy, health behaviors, and health outcomes at 6, 12, 18, and 24 months. Participants in the intervention group will be interviewed about their experiences. Conclusion: The APSC program can serve as an effective tool for facilitating diabetes health behaviors by improving patients' self-care self-efficacy and self-regulation for self-care. However, the clinical effectiveness of this program requires further investigation.