• Convergence Security Journal
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• v.24 no.2
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• pp.47-53
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• 2024

The traditional personal information life cycle model, primarily tailored to conventional systems, is inherently unsuitable for comprehending the nuances of personal information flow within artificial intelligence frameworks and for formulating effective protective measures. Therefore, this study endeavors to introduce a personal information life cycle model specifically designed for artificial intelligence (AI). This paper presents a personal information life cycle model suitable for artificial intelligence, which includes the stages of collection, retention, learning, use, and destruction/suspension, along with the re-learning process for destruction/suspension. Subsequently, we compare the performance of these existing models (such aspersonal information impact assessment and the ISMS-P model) with the newly proposed model. This underscores the superiority of our proposed model in comprehensively understanding the personal information flow in AI and establishing robust protective measures.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.1
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• pp.111-125
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• 2013

This study is to find out that how the personal, collective, and organizational learning method three learning organization affect the job satisfaction, organizational commitment, and innovative action through the questionnaire of company members, and to verify the moderating effects of shared values in this relation. The results show that three learning organization have a positive effect on the job satisfaction, and a partial effect on organizational commitment and innovative action, and shared values influence positively on the job satisfaction, organizational commitment, and innovative action. The moderating effects of shared values in the relation between three learning organization and Organizational Effectiveness are as follows : First, shared values can moderating the influence of collective and organizational learning organization on the job satisfaction, but can't moderating the relation between a personal learning method and the job satisfaction. Second, shared values can moderating the influence of collective and organizational learning organization on the organizational commitment, but can't moderating the relation between a personal learning method and the organization commitment. Third, shared values can moderating the influence of personal and organizational learning organization on the innovative action, but can't moderating the relation between the collective learning method and the innovative action.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.3
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• pp.71-78
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• 2001

Since web-based tutoring systems are generally composed with passive and static hypertext, they could not provide adaptive learning environments according to learning ability of each student. In this study, we suggest an intelligent tutoring system, which grasps the learning state of student and provides each student with dynamic learning materials suitable to individual feature based on learning result. It is an agent based system, in which, courseware knowledge for learning is effectively constructed, the proper feedback according to learning assessment is inferred, and it is given to each student.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.91-107
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• 2012

As the Internet becomes more popular, many people use it to communicate. With the increasing number of personal homepages, blogs, and social network services, people often expose their personal information online. Although the necessity of those services cannot be denied, we should be concerned about the negative aspects such as personal information leakage. Because it is impossible to review all of the past records posted by all of the people, an automatic personal information detection method is strongly required. This study proposes a method to detect or classify online documents that contain personal information by analyzing features that are common to personal information related documents and learning that information based on the Na$\ddot{i}$ve Bayes algorithm. To select the document classification algorithm, the Na$\ddot{i}$ve Bayes classification algorithm was compared with the Vector Space classification algorithm. The result showed that Na$\ddot{i}$ve Bayes reveals more excellent precision, recall, F-measure, and accuracy than Vector Space does. However, the measurement level of the Na$\ddot{i}$ve Bayes classification algorithm is still insufficient to apply to the real world. Lewis, a learning algorithm researcher, states that it is important to improve the quality of category features while applying learning algorithms to some specific domain. He proposes a way to incrementally add features that are dependent on related documents and in a step-wise manner. In another experiment, the algorithm learns the additional dependent features thereby reducing the noise of the features. As a result, the latter experiment shows better performance in terms of measurement than the former experiment does.

• The Journal of Korean Association of Computer Education
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• v.8 no.4
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• pp.49-56
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• 2005

Because e-learning system does not have any dynamic contents-delivery mechanism, all students in the same class get identical contents. In this paper, we introduce a personalized learning system, which is carefully designed and implemented based on data stream technology. The proposed system have a mechanism and interface changing lecture contents based on learner's level and ability. The system consists of a dynamic contents-delivery mechanism and learner level-test system. In this paper, we describe what are points to be considered when design and implementing a personalized learning system.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.764-767
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• 2024

웨어러블 디바이스에서는 사용자의 다양한 메타데이터를 수집할 수 있다. 그러나 이런 개인정보를 함유하고 있는 데이터를 수집하는 것은 사용자에게 개인정보침해 위협을 야기한다. 때문에 본 논문에서는 개인정보보호를 통한 웨어러블 디바이스 데이터활용방안으로 연합학습을 채택하였다. 다만 기존 연합학습에서도 해결해야할 문제점들이 있다. 우리는 그중에서도 데이터이질성(Data Heterogeneity) 문제해결을 위해 군집화(Clustering) 방법을 활용하였다. 또한 기존의 코사인유사도 기반 군집화에서 파라미터중요도가 반영되지 않는다는 문제점을 해결하고자 데이터수 기반 마하라노비스거리(Number of Samples Mahalanobis Distance) 군집화 방법을 제시하였다. 이를 통해 WESAD(Werable Stress Affect Detection)데이터에서 피실험자의 데이터 이질성이 존재하는 상황에서 기존 연합학습보다 학습 안정성 측면에서 좋음을 보여주었다.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.152-158
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• 2001

Since web_based tutoring systems are generally composed with passive and static hypertext, they could not provide adaptive learning environments according to learning ability of each student. In this study, we suggest an intelligent tutoring system, which grasps the learning state of student and provides each student with dynamic learning materials suitable to individual feature based on learning result. It is an agent based system, in which, courseware knowledge for learning is effectively constructed, the proper feedback according to learning assessment is inferred, and it is given to each student.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.592-594
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• 2000

오늘날과 같이 급변하는 사회 속에서 개인 혼자서 모든 일을 처리하기보다는 여러 사람과 함께 열린 사고로 일을 처리하는 것이 훨씬 효율적이다. 학습에서도 마찬가지로 협동학습은 지식뿐만 아니라 인성적인 면에도 영향을 끼치게 된다. 본 논문에서는 구성주의에 입각한 웹기반 협동학습 시스템을 설계 및 구현하여 실제 학습 수업에서 활용한다. 이 시스템에서는 학습내용을 구성하는 부분과 이를 이용하여 학습을 수행하는 부분들이 교수자간 및 학습자간에 협동을 한다. 이는 고차원적인 사고를 요구하는 문제해결학습을 통해 학습자 개개인의 능력을 최대한 개발할 수 있고, 학습 성취감을 증가시킬 수 있다. 또한 그동안 부족했던 웹상에서의 상호작용적인 측면을 강화하여 면대면 교육과 같은 즉각적인 효과도 얻을 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.983-985
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• 2013

본 논문에서는 학습자의 인지능력을 진단하고 이를 기반으로 하는 학습자 프로파일에 대하여 제안한다. 기존의 인지능력 측정방법으로는 알기 어려운 학습자의 세부적인 학습 능력을 적용한 학습자 프로파일은 지능형 튜터링 시스템의 최종적인 목표인 개개인의 맞춤형 학습 제공을 목적으로 학습자의 인지능력 측정 및 패턴분류를 통해 세부적인 학습자의 인지능력 측정하고 이를 기반으로 학습자 프로파일을 설계하였다.

• Communications of Mathematical Education
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• v.29 no.4
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• pp.723-743
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• 2015

In this research, The objective of the present study was to develop a preliminary diagnostic worksheet for use in consultations for learning mathematics. In order to achieve this, the worksheet was constructed with questions designed to assess the students. Through standardization, diagnostic worksheets for primary school students in grades 5 and 6 and secondary school students in grades 7 and 8 were produced. The diagnostic worksheet was divided into three sections, consisting of the psychology of learning mathematics in section 1, the methodology in learning mathematics in section 2, and personal preferences in learning mathematics in section 3. The psychology of learning mathematics was composed of questions on factors such as, "confidence in math learning ability," "math anxiety," and "attitude in learning mathematics." Moreover, factors in methodology in learning mathematics were "self-management in learning mathematics" and "math learning strategies." Those for personal preferences in learning mathematics asked about "motivation" and "preferences" with questions about "math learning habits" and "management methods for learning math." This diagnostic worksheet can be used as basic material in consulting students on learning mathematics.