• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.491-492
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• 2023

본 논문에서는 일상생활의 편의성을 높이기 위한 새로운 AI 애플리케이션 'Chat Chef'를 제안 한다. 이 앱은 사용자의 냉장고 속 재료 정보를 바탕으로 ChatGPT를 이용하여 요리 레시피를 추천하는 기능을 제공한다. 사용자는 앱을 통해 냉장고 내의 재료들을 사진으로 촬영하면, 이미지 인식을 위해 YOLOv7를 이용하여 감자, 당근, 양파 등과 같은 식료품들을 약 3,000장의 이미지 데이터를 학습하여 인식하며, 바코드를 인식하여 제품들 목록을 데이터베이스에 저장한다. 제안한 'Chat Chef' 앱은 재료 목록과 ChatGPT API를 이용하여 사용자에게 개인화된 레시피를 제공하며, 요리 과정에 대한 정보를 제공한다. 이와 같이 ChatGPT와 같은 AI 기술을 활용하여 실생활에 적용할 수 있는 활용 방안을 제시한다.

• Journal of the Korean Applied Science and Technology
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• v.37 no.3
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• pp.473-483
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• 2020

This paper proposes a tourism recommendation system in intelligent cloud environment using information of tourist behavior applied with perceived value. This proposed system applied tourist information and empirical analysis information that reflected the perceptual value of tourists in their behavior to the tourism recommendation system using wide and deep learning technology. This proposal system was applied to the tourism recommendation system by collecting and analyzing various tourist information that can be collected and analyzing the values that tourists were usually aware of and the intentions of people's behavior. It provides empirical information by analyzing and mapping the association of tourism information, perceived value and behavior to tourism platforms in various fields that have been used. In addition, the tourism recommendation system using wide and deep learning technology, which can achieve both memorization and generalization in one model by learning linear model components and neural only components together, and the method of pipeline operation was presented. As a result of applying wide and deep learning model, the recommendation system presented in this paper showed that the app subscription rate on the visiting page of the tourism-related app store increased by 3.9% compared to the control group, and the other 1% group applied a model using only the same variables and only the deep side of the neural network structure, resulting in a 1% increase in subscription rate compared to the model using only the deep side. In addition, by measuring the area (AUC) below the receiver operating characteristic curve for the dataset, offline AUC was also derived that the wide-and-deep learning model was somewhat higher, but more influential in online traffic.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.15-21
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• 2016

Under the flag of creative economy, Korea government is now releasing public data in order to develop or provide a range of services. In this paper, we develop a customized trip navigation system to recommend a trip itinerary based on integration of open government data and personal tourist data. The system uses case-based reasoning (CBR) to provide a personalized trip navigation service. The main difference between existing trip information systems and ours is that our system can offers a user-oriented information service. In addition, our system supports Turn-key style contents provision to maximize convenience. Our system can be a good example of the way in which open government data can be used to design a new service.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.117-123
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• 2012

Smart devices are great tool to get a lot of information of user by variety sensors, application, web. The information is good clue to seize pattern of user. So, we can expect that customized content-service will be possible based on utilizing information of user. This expectation alters the type of content-service from just providing lots of contents to smart devices to recommendation contents which wanted, needed, favorite looking by user. For this customized content-service, a system model like a curator in galleries or museums is required. So, in this paper, we suggest Intelligent Contents Curation(ICCuration) model which has 3 sub modules with sensing, analysis and filtering information of user. The collected information of user are processed up to scenarios and the scenario is a clue for selecting contents which will be recommended to users. In the scenario has user's preferences and behaviors as well as devices informations as elements. So, contents can be optimized not only domain category but type of media for devices.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.177-182
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• 2023

When determining a meeting place, it is always a cumbersome problem to select an appropriate store with a short travel time for all participants. In this paper, to solve this problem, we propose an algorithm that recommends the best place and store based on the subway station and develop the system. This system provides a web-based store information registration function that allows self-employed people to register and promote their store, and provides an app-based function to recommend a meeting place to participants. The proposed algorithm reduces the travel time of all participants based on the subway map and improves fairness by using the standard deviation of the required time. In addition, this system presents a new way for self-employed people who have recently relied only on publicity through delivery apps.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.89-106
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• 2017

In advanced mobile devices environment, the market share of mobile application has been increased. Among various mobile services, Location-based Service (LBS) is an important feature to increase user motivation related to purchase intention on mobile. However, individual privacy has also increased as an important problem for invasion of privacy and information leakage while too many LBS based applications (App) rapidly launched in the App market. In this study, we focused on perceived values of LBS App users who use Apps related to recommending best restaurants in China and South Korea. The purpose of this study is to identify important factors for perceived value when users provide personal information for LBS service provider. The result of this study is follows: perceived value can increase while LBS customers can more control self-information and information useability. Also information ability of users affected perceived values for LBS Apps. Also users' app user ability and perceived value were effects on privacy revenue. In addtion, perceived weakness of users and perceived value increased privacy threat.

• Electronics and Telecommunications Trends
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• v.29 no.3
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• pp.11-16
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• 2014

방송과 통신이 융합되면서 새로운 서비스들이 등장하고 있는데 서비스만 보고서는 방송서비스인지 통신서비스인지 분간이 힘든 기술들이 다수 등장하고 있다. 최근 스마트TV가 방송, 통신, 컴퓨팅의 대표적인 서비스로 부각되면서 멀티플랫폼 연동의 하이브리드 미디어서비스가 다양하게 개발되고 있다. 본 논문에서는 방송통신 융합서비스에 대해서 두 매체 간의 연관여부에 따라 2가지로 서비스를 분류하고 각 분류된 방식에 따른 다양한 하이브리드 미디어서비스의 실제 구현사례를 소개한다. 소개되는 서비스에는 개인형 홈스크린, 앱스토어, 콘텐츠 검색 및 추천, 패밀리톡, 대면 통신을 포함하는 스마트TV 홈스크린 기반 미디어 융합서비스와 하이브리드광고 서비스, 멀티앵글뷰 서비스, 멀티오디오 서비스를 포함하는 스마트TV 하이브리드 미디어서비스이다. 본 논문에서는 모든 서비스가 HTML5 기반의 웹브라우저에서 동작하도록 구현하였다.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.93-99
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• 2019

It is a wine recommendation application service designed for people who sometimes drink wine but lack information and have no place to recommend. This study is to develop UI display design method of wine recommendation service using chatbot. The research method was a case study on Korean wine market, a case study on artificial intelligence market, SWOT analysis of wine-related chatbots, and a competitor analysis of related industries. In addition, surveys and in-depth interviews examined the level of interest and understanding of chatbots, and what kind of chatbots they had encountered and what requirements and goals they faced. After grasping the needs and requirements of users, we created a service concept sheet according to them and produced an application UI design that users can use most easily. Therefore, this study is meaningful in that it proposes a UI design that can search wine information more sophisticated and convenient than face-to-face communication through artificial intelligence service called chatbot and recommend wines that match the taste.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.712-713
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• 2015

IoT (Internet of Things)가 차세대 기술로 각광을 받으면서 않은 IT 전문인들이 대표주자인 웨어러블 디바이스(wearable device) 의 활용도에 많은 관심을 기울이고 있다. 하지만 현재까지 헬스케어(healthcare)와 피트니스(fitness) 서비스 중심으로 구성되는 등 다양성을 갖지 못하고 있다. 본 논문에서는 스마트 위치를 이용하여 장보기에 다양한 편리성을 제공하는 라이프스타일 관련 웨어러블 어플리케이션을 제안한다. 바코드 스캐닝 기능을 통하여 구매한 제품에 대한 정보를 자동으로 검출하여 가계부를 작성한다. 또한 고객에게 현재까지의 구매 내역에 기반하여 최적의 추천상품 목록을 구성하는 서비스도 제공한다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.69-78
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• 2019

The amount of data is increasing significantly as information and communication technology advances, mobile, cloud computing, the Internet of Things and social network services become commonplace. As the data grows exponentially, there is a growing demand for services that recommend the information that users want from large amounts of data. Collaborative filtering method is commonly used in information recommendation methods. One of the problems with collaborative filtering-based recommendation method is the cold start problem. In this paper, we propose a method to improve the cold start problem. That is, it solves the cold start problem by mapping the item evaluation data that does not exist to the initial user to the automatically generated data from the mobile app. We describe the main contents of the proposed method and explain the proposed method through the book recommendation scenario. We show the superiority of the proposed method through comparison with existing methods.