• Proceedings of the Korean Information Science Society Conference
• /
• 2005.07b
• /
• pp.361-363
• /
• 2005

본 연구에서는 온라인 다중 사용자 환경의 eBook 어노테이션 시스템 개발에서 데이터를 의미 기반으로 관리하고, 데이터에 대하여 상호 공통적인 이해를 표현하며, 그리고 데이터에 대한 무결성 검사 등을 지원하기 위해서 eBook 어노테이션 온톨로지를 구축하였다. eBook 어노테이션 테이터에 대한 상호 공통적인 이해의 표현을 위해서 한국 전자책 문서 표준인 EBKS(Electronic Book of Korea Standard)를 기반으로 구축 하였으며 구축된 온톨로지는 Conceptual Graph(CG)를 사용하여 표현하였다. 의미 기반의 처리를 위해서 본 온톨로지에서는 다국어(Multilingua) 관계를 고려하였으며 또한 오노테이션 데이터 생성 시 중요도를 표현하기 위해서 중요성 axiom을 고려했고, $NF^2$(Non-First Normal Form)에 입각하여 온톨로지를 설계함으로서 어노테이션 데이터의 검색에 활용도를 높였다. 제안된 온톨로지는 어노테이션 데이터의 재사용성을 높일 수 있고 의미 정보를 활용함으로써 eLearning, cyberclass과 같은 다중 사용자 환경에서 효과적인 협업을 가능하게 한다. 본 연구에서는 구현한 eBook annotation 시스템은 구축한 온톨로지를 사용함으로써 의미 기반의 데이터 관리가 가능하다. 또한 어노테이션 생성 시 온톨로지 구조를 모르더라도 어노테이션을 생성할 수 있는 인터페이스를 구현하였다.

• Journal of Internet Computing and Services
• /
• v.14 no.2
• /
• pp.15-24
• /
• 2013

In recent years, the number of social network system has grown rapidly. Among them, social bookmarking system(SBS) is one of the most popular systems. SBS provides network platform which users can share and manage various types of online resources by using tags. In SBS, it can be possible to reflect tag and time in order to enhance the quality of personalized recommendation. In this paper, we proposed recommender system which reflect tag and time at weight generation and similarity calculation. Also we adapted proposed method to real dataset and the result of experiment showed that the our method offers better performance when such information is integrated.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10a
• /
• pp.552-556
• /
• 2006

항공우주의 연구를 위해 대용량의 컴퓨팅 자원 이용, 실험 결과의 상호 교류 및 분석, 온라인 상에서의 자동 실행 등의 서비스가 요구된다. 본 논문에서는 이미 개발된 e-AIRS[1],[2]의 활용을 극대화하고 병렬해석에 많이 사용되고 있는 동적 파라메터 실험 서비스를 구현하고자 한다. 동적 파라메터 실험 서비스는 복잡한 현상을 포함한 다양한 계산 수행을 지원하기위해, 동적으로 파라메터를 생성하고 효율적으로 동시에 작업들을 실행하는 서비스이다. 또한 GT4(Globus Toolkit 4)[3] WSRF를 기반으로 웹 서비스로 구현하여 서비스의 이용 및 접근을 용이하게 하고자 한다. 연구자간의 효과적인 정보 공유 및 협의 서비스를 제공함으로써 항공 우주 연구 개발에 있어 효율적인 환경을 지원함은 물론 연구자간 협력을 통한 신뢰성 있는 결과 값을 도출할 수 있도록 하고 있다.

• The Journal of Information Systems
• /
• v.29 no.4
• /
• pp.123-135
• /
• 2020

Purpose The purpose of this study is to investigate the development process and the effectiveness of the EISS (epidemiological investigation support system), which prevents the spread of infectious diseases like a novel corona virus disease, COVID-19. Design/methodology/approach This study identified the existing epidemiological support system for MERS through prior research and studied the case of the development of a newly developed epidemiological support system based on cloud computing infrastructure for COVID-19 through inter-ministerial collaboration in 2020. Findings The outbreak of COVID-19 drove the Korean Government began the development of the EISS with private companies. This system played a significant role in flattening the spread of infection during several waves in which the number of confirmed cases increased rapidly in Korea, However, we need to be careful in handling confirmed patients' private data affecting their privacy.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2021.01a
• /
• pp.85-87
• /
• 2021

컴퓨터 전공자들의 프로그래밍 개발 중심의 팀 프로젝트 수업은 프로그래밍 개발 능력과 팀원들 간의 협업 능력을 키울 수 있는 수업으로서, 기존에는 대면수업을 통해 교수자와 학습자간 그리고 팀을 이룬 학습자들 간에 긴밀한 상호작용으로 진행되어왔다. 그러나 2020년 COVID-19의 확산으로 대부분의 대학 수업들이 비대면 방식으로 진행됨에 따라 팀 프로젝트 수업 역시 비 대면으로 운영되어야 했으며 팀 활동을 위해 다양한 온라인 커뮤니케이션 방법이 모색되어야 했다. 본 연구에서는 팀 프로젝트 수업을 기존의 대면 수업으로 운영하였을 경우와 비대면 방식으로 운영하였을 때 학습자들이 느끼는 학습 효과에 대해 비교해보고자 한다. 대면 수업과 비대면 수업에 참여했던 학습자들을 대상으로 설문을 실시하여 팀 프로젝트 수업을 통한 학습 이해도, 수업 흥미도, 학습자간의 소통의 원활성, 수업 참여의 적극성 그리고 전체적인 수업 만족도에 대한 설문 결과를 비교 분석하였다. 향후 포스트 코로나 시대에는 대면과 비대면의 하이브리드 커뮤니케이션 방식이 대세를 이룰 것으로 예측되고 있는 만큼 대학 수업 방식에도 변화가 필요할 것이며 본 연구는 이를 위한 기초 연구로 활용될 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2022.06a
• /
• pp.1-3
• /
• 2022

코로나 19 팬데믹으로 인한 4차 산업혁명이 앞당겨지고 초현실, 초실감, 초연결 사회 등의 키워드가 대두되고 언택트(Untact) 시대가 일상생활에 불가항력적으로 접목되면서 몰입감과 흥미성, 유희성을 목적으로 한 콘텐츠들이 다양하게 활성화되었다. 특히, 메타버스(Metaverse) 플랫폼이 빠르게 진화하면서 물리적 현실과 디지털 가상성을 융합한 다중 사용자에게 다양한 경험이 가능한 서비스가 주목받고 있다. 메타버스는 다중 사용자 플랫폼에서 원활한 커뮤니케이션과 대규모 멀티플레이가 가능한 온라인 비디오 게임, 오픈 게임 월드, AR 협업 공간과 호환되는 사회적, 몰입감이 있는 VR(Virtual Reality) 플랫폼 서비스 중 하나이다. 우리는 메타버스 플랫폼 개발 시 필요로 하는 요소기술 및 3D 데이터 획득을 통한 VR 콘텐츠를 설계하고 구현하고자 한다. 1) 콘텐츠 시나리오 및 사용자 인터랙션 설계; 2) 볼류메트릭 캡처를 활용한 실사 기반의 동적(Dynamic) 데이터 생성; 3) 컴퓨터 그래픽 기반 가상공간 설계 및 정적(Static)데이터 요소기술 개발; 4) 가상 현실 공간 데이터와 볼류메트릭 캡처의 실사 데이터 정합; 5) 공간 데이터 시각화 생성 및 모듈형 공간 이동 제어 기능 개발; 최종적으로 6) VR 환경에서의 콘텐츠 구현을 목표로 한다.

• Journal of Practical Engineering Education
• /
• v.15 no.2
• /
• pp.233-241
• /
• 2023

This study analyzes the construction status of digital employment services in Korea and presents the direction of continuous advancement and development of digital employment services based on overseas cases and the latest digital technology development trends. Find out the specific digitalization promotion strategies and current status of major countries such as Belgium, Australia, the United Kingdom, Germany, France, and the United States. In addition, in order to present a plan for the development of digital employment services in Korea, we will propose a plan to expand digital employment services to online employment centers through individual and customized employment services, data openness, and expansion of public-private collaboration through digital employment services using AI and big data.

• Journal of Korean Home Economics Education Association
• /
• v.32 no.4
• /
• pp.149-170
• /
• 2020

The purpose of this study was to develop and evaluate a Smart learning-based middle school home economics education plan to improve the online home economics education classes. The educational plan in this study was completed through the process of analysis, design, development, and evaluation. The results of this study are as follows. First, as a result of analyzing consumer life units in the middle school textbooks based on 2015-revised curriculum, Smart learning activities were presented in only two out of the 12 textbooks analyxed. Second, a Smart learning-based middle school home economics education plan was developed in this study with the following characteristics: the topics and contents are structured so that to help learners actively engage in the teaching and learning activities; the education plan to reflects various media and current issues that learners may be interested in; the lesson plans were structured with the premise of online classes; softwares that enable real-time discussion and collaboration are used; and the evaluation method are composed of online activities. Third, the expert evaluation scores for the educational plan and activity materials developed were 4.52 (5-point Likert scale), when averaged across subject, goal, content, teaching/learning activity, and evaluation, and the overall content validity index(CVI) was 0.95. The adequacy of execution, benefit, attractiveness, usefulness, and feasibility were highly with an average of 4.62. Based on the experts' comments, the education plan and activity materials were revised and completed. This study is meaningful in that it developed teaching and learning activities based on online classes after the COVID-19 outbreak, overcoming the limitations of offline classes. It has implications for face-to-face home economics classes due to COVID-19, as it suggests ways to blend online and offline teaching/learning activities depending on the situation.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.85-109
• /
• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.276-279
• /
• 2022

The 4th industrial revolution refers to the transition to a knowledge society in which the production speed of knowledge is fast and the proportion of the knowledge industry is greatly increased. The reorganization of the industrial structure and the change of occupations and jobs due to new technologies are bringing about changes in education, and the development of digital technology has made education that is borderless, individual and dynamic, becoming the new standard of education. With these changes, interest in nano-degrees on new technologies or micro-degrees focused on core courses rather than regular course degrees is increasing. As a representative example, Udacity in the United States has opened and operated online nanodegree courses related to jobs, and collaborates with major companies to develop and educate core training courses necessary for companies, thereby efficiently supporting companies in securing talent. With the revitalization of online vocational and job training, an environment has been prepared in which individuals can set goals for vocational competency development and continue their portfolio-based sustainable learning. However, for effective vocational education, automated and personalized educational content design should be preceded. To this end, in this paper, we propose a personalized career and course map recommendation system in the era of online learning