• Journal of the Korea Convergence Society
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• v.5 no.4
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• pp.147-153
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• 2014

To create a personal menu, there are a number of considerations. Personal menus are different depending on the dietary therapy for disease, diet for weight control. In addition, the menu you choose, depending on the personal preference and the season, the weather, current personal feelings may differ. An individual should expect to recommend a balanced diet, taking nutritional status just for health care. In this paper, we propose a personalized menu recommendations System framework to meet such needs. To recommend menus the system receives data of the body's individual circumstances, ingredients situation, environmental conditions, psychological condition, emotional condition and provides a recommended menu by performing the inference using the ontology generated from external application systems. In order to provide such services, Internet of Things (IoT) environment should be the foundation. In this paper, we propose a personalized diet recommendation system framework in the IoT standardization environment that has oneM2M common service platform.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.496-499
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• 2018

최근 서구화된 식습관으로 인해 국내 비만 인구가 급격하게 증가했고 이에 따라서 다이어트에 관심을 갖는 사람들이 많아졌다. 하지만 현재 출시되어 있는 애플리케이션은 단지 식단을 선택하도록 목록을 보여주는 것에 그친다. 최근 추천 시스템은 데이터 서비스에 필수적인 요소가 되었고 사용자가 직접 선택에 대한 고민 할 것 없이 개인에게 맞춤된 식단을 제공 할 필요가 있다. 따라서 본 논문에서는 FatSeceret Open-API를 사용하여 추출한 식품 데이터베이스를 통해 사용자의 식단 선호도를 분석하였다. 그래서 식단 선호도와 협업 필터링 기법을 R을 이용하여 개인 맞춤형 다이어트 식단을 추천해 주는 시스템을 개발한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.187-188
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• 2020

본 논문에서는 한방 8체질 및 신체정보 관련 데이터셋을 바탕으로 개인 맞춤 식품 및 식단을 추천하는 데이터베이스의 설계·구축을 수행한다. 또한 이 시스템을 이용하여 추천된 식품(식단)과 희망하는 지역을 입력했을 때 선별된 음식점 정보를 제공한다. 데이터베이스 생성 프로세스와 수집한 데이터를 통해 데이터베이스 설계, 데이터 수집, 생산 및 처리 예제, 데이터베이스 활용 등에 대해 다양한 방법을 제공한다. 일상생활에서 데이터베이스 시스템을 활용함으로써, 이 시스템은 한의원 또는 전문채널을 통해 알 수 있었던 맞춤 식단 정보를 대중에 공개되어 정보 진입장벽을 낮추고 편의성을 도모한다. 이로써 오늘날 고령 사회에 진입한 대한민국에서 국민들이 건강한 식생활을 지원하여 궁극적으로 국민 건강 증진에 기여한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.199-208
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• 2023

The National Health Insurance Corporation reported a 24.3% increase in young diabetes patients, rising to 3,564,059 in 2021 from 2017, which is attributed to factors like irregular eating patterns, heightened stress, and insufficient physical activity. Diabetes, which is increasing in all age groups, requires medication, regular exercise, and dietary management. Of these aspects, dietary therapy demands systematic management as it involves ensuring sufficient calorie intake and a balanced consumption of the three major nutrients. The current diabetes diet recommendations consider personal, health, social, and cultural factors, yet they fall short of addressing various health variables comprehensively. Therefore, this paper proposes a diet recommendation system using life log data from diabetic patients, which recommends customized dietary suggestions according to the individual's health status by considering multiple variables in the data.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.1109-1115
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• 2012

In this paper, we propose a system that recommends the appropriate menu using the fuzzy rules and the case database. The rules are defined by using the user's body information such as height and weight and these information is often vague. Due to its fuzziness, we use the fuzzy logic to represent the information. In our system, it firstly gets the body information for computing the BMI (Body Mass Index) values. Then it combines the muscle mass factor and BMI values to make a fuzzification for calculating the obesity rate. It finally recommends the most relative menu by comparing with the user's obesity rate from each cases in the database. We implement the system on the Android platform and show that our proposed method can achieve reasonable performance through the various experiments,

• KIPS Transactions on Software and Data Engineering
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• v.6 no.3
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• pp.161-166
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• 2017

In recent times, many people have problems of nutritional imbalance; lack or surplus intake of a specific nutrient despite the variety of available foods. Accordingly, the interest in health and diet issues has increased leading to the emergence of various mobile applications. However, most mobile applications only record the user's diet history and show simple statistics and usually provide only general information for healthy diet. It is necessary for users interested in healthy eating to be provided recommendation services reflecting their food interest and providing customized information. Hence, we propose a menu recommendation method which includes calculating the recommended calorie amount based on the user's physical and activity profile to assign to each food group a substitution unit. In addition, our method also analyzes the user's food preferences using food intake history. Thus it satisfies recommended intake unit for each food group by exchanging the user's preferred foods. Also, the excellence of our proposed algorithm is demonstrated through the calculation of precision, recall, health index and the harmonic average of the 3 aforementioned measures. We compare it to another method which considers user's interest and recommended substitution unit. The proposed method provides menu recommendation reflecting interest and personalized health status by which user can improve and maintain a healthy dietary habit.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.435-442
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• 2016

Obesity extends the global economic burden and it causes that the failure of a reduction of physical activity, and diet management. In this work, nutritional information and personalized diet based on calorie supply system and is discriminatory utilized the obesity-related SNP information in order to recommend a personalized functional foods. This study performed a GWAS analysis for the excavation of a Korean-specific and obesity-related SNP, which utilizes genetic information were recommended by entering a personalized diet in accordance with the SNP genotype-phenotype information. In addition, we integrated Database with relation of nutrient for utilizing the USDA Food information and it was applied to recommend with Sickdanome. As a result, the obesity-related SNP information was confirmed in the sample which has the normal value BMI. In this study, we have recognized that the phenotype information related obesity, BMI is inconsistent with the SNP genotype information. This result is shown that it is necessary to provide the personalized dietary SickdanOme recommendation based on the both pheotype-genotype information.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.111-119
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• 2010

U-Healthcare provides healthcare and medical services, such as prevention, diagnosis, treatment, and follow-up services whenever and wherever it is needed, and its ultimate goal is to improve quality of life. This study defines the figure of U-Healthcare personalized services for providing U-Healthcare personalized services and proposes a healthcare model. A diet prescription system for personalized services can draw customized calories and rates of nutrition factors and represent a personalized diet through analyzing the personal preference in foods. This system changes the personal preference by monitoring the diet selection behavior of users. Also, this system is designed to be interactively operated with some sensors and devices in various environments using Java-based OSGi middleware.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.359-361
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• 2022

최근 현대인의 영양불균형이 점점 심화됨에 따라 영양결핍과 비만의 위험도가 점점 증가하고 있다. 이에 따라 건강기능식품에 대한 관심이 증가하여 일반인들의 건강기능식품 소비가 증가하고 있지만, 적정섭취량에 비해 영양소를 과도하게 섭취 중이거나 영양제를 먹지만 정작 필요한 영양소를 섭취하지 못하는 경우가 빈번히 나타나고 있다. 이러한 문제를 해소하고자 본 논문에서는 7 일간 사용자가 섭취한 식단을 기반으로 부족한 영양소를 수치상으로 계산하여 개인 맞춤 영양제를 추천하는 시스템을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.138-140
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• 2022

시스템은 음식 알레르기가 있는 사용자에게 제공되는 식단을 계획하거나 제공할 때 음식, 식품 또는 레시피에 알레르기 성분이 있는지를 확인하고 표시함으로써 음식 알레르기를 예방할 수 있으며, 더 나아가 음식 알레르기의 대체 식품을 추천하고 선택하는 기능을 제공한다. 또한 음식 영양성분 및 열량을 재산정 함으로써 영양균형을 이룰 수 있는 환경을 제공한다.