• Digital Contents
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• no.4 s.143
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• pp.62-63
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• 2005

학습자가 원하는 학습자원을 컴퓨터가 스스로 찾아내서 학습자에게 전달해주고, 더 나아가 새로운 지식까지 추론해서 제공해 줄 수는 없을까? 살아 있는 e러닝이 되기 위해서는 컴퓨터가 학습자가 원하는 학습자원의 의미를 이해하고, 적시적(Just-in-time)으로 학습자에게 맞는 형태(Just-for-me)로 학습자원을 제공해 주어 학습이 단편적이 아닌 연속적, 통합적으로 이뤄질 수 있는 적응적 학습 환경이 필요하다.의미의 웹이라 불리 우고 있는 시멘틱 웹(Semantic Web)은 의미적으로 연결돼 있는 학습 정보를 컴퓨터가 의미를 이해해서 학습자가 원하는, 학습자 수준에 맞는 정보를 제공해주고, 더 나아가 지식까지도 추론해서 학습자에게 가장 적합한 형태로 전달해 줄 수 있는 강력한 매카니즘으로 부각되고 있다. 이에 필자는 살이 있는 e러닝이 되기 위해서는 시멘틱 웹과의 통합이 필요하다고 생각해 2회에 걸쳐 시멘틱 웹과, 시멘틱 웹을 e러닝에 어떻게 적용할 것인지에 대해 애기해 보고자 한다.

• Annual Conference of KIPS
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• 2002.11c
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• pp.2463-2466
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• 2002

본 연구에서는 학습자의 수준에 맞는 적합한 학습 내용과 평가 문제를 제공하고, 그 평가 결과를 분석하여 반복학습 및 심화학습을 효과적으로 제공하는 웹기반 퍼지 교수 시스템을 제안한다. 이를 위해 코스웨어를 설계시 학습목표의 중요도, 학습내용의 난이도, 학습목표와 학습내용과의 관련성과 각 항목의 가중치를 고려한 퍼지 함수에 의해 퍼지 소속성을 가진 퍼지 언어 변수로 각 프레임에 대한 수준을 표현한다. 이와 같이 퍼지 함수를 이용함으로써 학습자의 수준을 분석하고, 이에 적절한 학습 및 평가 내용을 제공하는데 여러가지 다양하고 불확실한 요소들을 고려하여 처리함으로써 보다 융통성 있고 효과적인 교수 학습 방법을 지원할 수 있다.

• Journal of KIISE:Software and Applications
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• v.34 no.6
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• pp.539-548
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• 2007

Mobile content adaptation is a technology of effectively representing the contents originally built for the desktop PC on wireless mobile devices. Previous approaches for Web content adaptation are mostly device-dependent. Also, the content transformation to suit to a smaller device is done manually. Furthermore, the same contents are provided to different users regardless of their individual preferences. As a result, the user has difficulty in selecting relevant information from a heavy volume of contents since the context information related to the content is not provided. To resolve these problems, this paper proposes an enhanced method of Web content adaptation for mobile devices. In our system, the process of Web content adaptation consists of 4 stages including block filtering, block title extraction, block content summarization, and personalization through learning. Learning is initiated when the user selects the full content menu from the content summary page. As a result of learning, personalization is realized by showing the information for the relevant block at the top of the content list. A series of experiments are performed to evaluate the content adaptation for a number of Web sites including online newspapers. The results of evaluation are satisfactory, both in block filtering accuracy and in user satisfaction by personalization.

• The Journal of the Acoustical Society of Korea
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• v.11 no.3
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• pp.40-52
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• 1992

In this paper, we propose the speaker adaptive word recognition method using a mapped membership function, in order to absorb a fluctuation owing to personal difference which is a problem of speaker independent speech recognition. In the training procedure of this method, the mapped membership function is made with the fuzzy theory introducded into a mapped codebook, between an unknown speaker's spectrum pattern and a standard speaker's one. In the recognition procedure, an input pattern of an unknown speaker is reconstructed to the pattern which is adapted to that of a standard speaker by the mapped membership function. To show the validity of this method, word recognition experiments are carried out using 28 DDD area names. The recognition rate of the conventional speaker-adaptive method using a mapped codebook by VQ is 64.9[%], and that made by a fuzzy VQ is 76.2[%]. Throughout the experiment using a mapped membership function, we can achieve 95.4[%] recognition rate. This shows that our proposed method is more excellent in recognition performance. Moreover, this method doesn't need an iterative training procedure to make the mapped membership function, and memory capacity and computation requirements for this method are reduced to 1/30 and 1/500 time of those for the conventional method using a mapped codebook, respectively.

• 한국정보교육학회:학술대회논문집
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• 2005.08a
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• pp.98-106
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• 2005

정보통신의 발달로 교육이 학습자 중심의 형태로 바뀌어 가면서 학습자의 자기 주도적인 능력이 점점 중요해지고 있다. 인터넷 학습환경에서도 학습자가 통제권을 가지고 학습자가 모든 선택과 조직을 할 수 있도록 허용되어 학습자는 학습방향의 상실과 인지적 부담의 문제를 초래한다. 이러한 문제를 해결 할 수 있는 방법 중의 하나가 학습자 특성에 맞는 교육이다. 본 연구에서는 장이론에 따라 학습자 특성을 구분하고 장의존 학습자에게 적응적인 웹 코스웨어 설계요소를 반영하여 웹 코스웨어의 설계전략을 탐구하였다.

• Journal of KIISE
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• v.44 no.8
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• pp.842-853
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• 2017

Streaming data is a sequence of data samples that are consistently generated over time. The data distribution or concept can change over time, and this change becomes a factor to reduce the performance of a classification model. Adaptive incremental learning can maintain the classification performance by updating the current classification model with the weight adjusted according to the degree of concept drift. However, selecting the proper weight value depending on the degree of concept drift is difficult. In this paper, we propose a dynamic ensemble method based on adaptive weight adjustment according to the degree of concept drift. Experimental results demonstrate that the proposed method shows higher performance than the other compared methods.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.111-119
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• 2014

The cloud environment need resource management method that to enable the big data issue and data analysis technology. Existing resource management uses the limited calculation method, therefore concentrated the resource bias problem. To solve this problem, the resource management requires the learning-based scheduling using resource history information. In this paper, we proposes the ART (Adaptive Resonance Theory)-based adaptive resource management. Our proposed method assigns the job to the suitable method with the resource monitoring and history management in cloud computing environment. The proposed method utilizes the unsupervised learning method. Our goal is to improve the data processing and service stability with the adaptive resource management. The propose method allow the systematic management, and utilize the available resource efficiently.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.178-186
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• 1996

We develop a simple adaptive population coding model for neural networks based upon an error minimization method. Our model exhibits properties that have been experimentally observed in the population coding of the motor-cortical cells during the voluntary arm movements of primates. By removing a group of directionally tuned cells after learning, we study its contribution to the population coding. Through the learning process of the remained cells, we observe how the cells modify their preferred directions to reduce the coding errors. Since this adaptive property has been neither predicted nor experimentally observed before, it would be interesting to find whether a similar adaptive property exists in real cortices that are believed to encode the information in their cell populations.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.736-741
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• 2006

The design of a classification system generally involves data acquisition module, learning module and decision module, considering their functions and it is often an important component of intelligent systems. The learning module provides a priori information and it has been playing a key role for the classification. The conventional learning techniques for classification are based on a winner take all fashion which does not reflect the description of real data where boundarues might be fuzzy Moreover they need all data for the learning of its problem domain. Generally, in many practical applications, it is not possible to prepare them at a time. In this paper, we design an adaptive classification model using incremental training fuzzy neural networks, FNN-I. To have a more useful information, it introduces the representation and membership degree by fuzzy theory. And it provides an incremental learning algorithm for continuously gathered data. We present tie experimental results on computer virus data. They show that the proposed system can learn incrementally and classify new viruses effectively.

• Communications of Mathematical Education
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• v.11
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• pp.47-69
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• 2001

본 논문은 고등학교 교육과정상에서 학습자들이 오류를 범하기 쉽고, 어려워 하는 극한에 대해 보다 효과적인 지도방법을 제시한다. 현실적으로 교수활동은 교실이라는 공간에서 일정한 수업시간동안에 교사와 학습자와의 관계속에서 이루어진다. 그 속에서 학습자들은 주변의 세계를 관찰함으로써, 혹은 추측과 반박을 통해 시행착오적으로 사고함으로써 혹은 모순, 어려움, 불균형을 일으키는 주위환경에 동화 ${\cdot}$ 조절을 함으로써 자신을 적응시켜 가면서 학습하게 된다. 따라서 교수학적 의도가 미비한 환경은 학습자에게 획득하기를 기대하는 학습을 할 수 없게 한다. Brousseas의 교수학적 상황론에 근거하여 교육의 현장인 교실에서의 교사와 학생간의 상호작용에 따른 교수-학습의 중요성에 초점을 둔 본 논문은 Freudenthal의 역사발생적 원리에 의한 극한의 정의와 학습자의 오류수정을 위한 교수학습 전략으로 Lakatos의 발견술을 제안하였다. 또한 극한 개념에 대해 실생활에서 학습자에게 쉽게 동화 ${\cdot}$ 조절이 일어날 수 있는 학습 방법을 제안하였다.