• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.103-105
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• 2003

Semantic Web은 웹 상에 존재하는 정보들을 사람뿐만 아니라 컴퓨터 프로그램과 같은 기계들이 이해할 수 있도록 만들어진 차세대 웹이다. 이러한 Semantic Web을 수행하기 위해서는 Ontology가 가지고 있는 사실과 규칙들의 의미를 컴퓨터가 자동적으로 이해하기 위한 추론기술이 필요하다. 본 논문에서는 이러한 Semantic Web 환경에서 Ontology와 연계한 사례기반 추론 시스템을 제안한다. 사례기반 추론 시스템은 사례베이스로부터 현재 사례와 가장 유사한 사례를 검색하여 그 해결책을 제시하는 추론 방법으로 검색시 빠른 해결책을 제시한다는 장점을 가지고 있다. 본 논문에서 제안하는 시맨틱 웹 기반의 온톨로지를 이용한 사례기반 추론시스템은 사용자의 요구사항을 의미적으로 정확하게 판단 할 수 있고, 검색 시 효율적인 알고리즘을 수행하여, 검색 성능 향상을 도모하였다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.571-578
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• 2005

Corporate credit rating analysis has drawn a lot of research interests in previous studies, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper applies support vector machines (SVMs) to the corporate credit rating problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, the researcher uses a grid-search technique using 5-fold cross-validation to find out the optimal parameter values of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM, the researcher compares its performance with those of multiple discriminant analysis (MDA), case-based reasoning (CBR), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1242-1247
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• 2009

The sudden changes in the construction market and the progressively intensifying price wars have amplified the importance of the construction cost estimation in the initial and planning phases of construction projects. However the methodologies and process of estimating construction cost in the planning and design phase are not standardized in the domestic market, in contrast to the markets of more developed countries. Therefore this paper proposes a new approximate estimation model to be used from the initial stages of construction projects. This methodology that extracts, modifies and synthesizes comparable elements of previous cases. This will introduce the foundation for the implementation of systems with improved usability and applicability.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.66-75
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• 1997

A fault diagnosis system for a variable speed rotating shaft probably demands a huge database, which makes it diffcult to be realized. This stuydy presents an effective method of fault diagnosis for variable speed rotating shafts. The proposed method is based upon a fuzzy reasoning and it includes a stepwize strategy to reduce the size of database in a diagnosis system. A computer program is developed to show the procedure of the diagnosis, and four cases of faults are applied to the program to illustarate the effectiveness of the proposed method. The propsed method is found to be useful in reducing the size of database from observation of the data files of the dianosis system. The case studies show that the proposed method can be useful for the diagnosis of variable speed rotating shafts.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.391-398
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• 1999

사례기반 추론을 포함한 Lazy Learning 방법들은 인공신경망이나 의사결정 나무와 같은 Eager Learning 방법들과 비교하여 여러 가지 상대적인 장점을 가지고 있다. 그러나 Lazy Learning 방법은 역시 상대적인 단점들도 가지고 있다. 첫째로 사례를 저장하기 위하여 많은 공간이 필요하며, 둘째로 문제해결 시점에서 시간이 많이 소요된다. 그러나 보다 심각한 문제점은 사례가 관련성이 낮은 속성들을 많이 가지고 있는 경우에 Lazy Learning 방법은 사례를 비교할 때에 혼란을 겪을 수 있다는 점이며, 이로 인하여 분류 정확도가 크게 저하될 수 있다. 이러한 문제점을 해결하기 위하여 Lazy Learning 방법을 위한 속성 가중치 부여 방법들이 많이 연구되어 왔다. 그러나 기존에 발표된 대부분의 방법들이 속성 가중치의 유효 범위를 전역적으로 하는 것들이었다. 이에 본 연구에서는 새로운 지역적 속성 가중치 부여 방법을 제안한다. 본 연구에서 제안하는 속성 가중치 부여 방법(CBDFW : 사례기반 동적 속성 가중치 부여)은 사례별로 속성 가중치를 다르게 부여하는 방법으로서 사례기반 추론의 원리를 속성 가중치 부여 과정에 적용하는 것이다. CBDFW의 장점으로서 (1) 수행 방법이 간단하며, (2) 논리적인 처리 비용이 기존 방법들에 비해 낮으며, (3) 신축적이라는 점을 들 수 있다. 본 연구에서는 신용 평가 문제에 CBDFW의 적용을 시도하였고, 다른 기법들과 비교에서 비교적 우수한 결과를 얻었다.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.74-82
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• 2007

Context awareness using intelligent system is emphasized in order to provide automatic services in home automatic system. In this paper, we propose the intelligent context-aware system for home automation. To implement home automation, we first collect various events occuring in user's home, which are saved as a case form. We use the saved data as a training data of a neural network algorithm and then apply to intelligent context aware system for home automation. This system provide "right situations do right things" for user. Also this system has intelligent ability.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2007.04a
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• pp.101-104
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• 2007

As the proportion of underground construction increases, the impact of inappropriate selection of a underground construction method for a construction size increases. The purpose of this study is to develop an objective way of selecting an excavation method. There have been several attempts to achieve the same goal using various data mining methods such as the artificial neural network, the support vector machine, and the case-based reasoning. However, they focused only on the selection of a retaining wall construction method out of six types of retaining walls. When we categorized an underground construction work into four groups and added more number of independent variables (i.e., more number of construction methods), the predictability decreased. As an alternative, we developed a decision tree by analyzing 25 earthwork cases with detailed information. We implemented the developed decision tree as a computer-supported program called Dr. underground and are still in the process of validating and revising the decision tree. This study is still in a preliminary stage and will be improved by collecting and analyzing more cases.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.929-936
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• 2004

A major limitation of available component-based platforms Is that they do not provide suitable means for describing and reasoning on the concurrent behaviour of interacting component-based system. Indeed while these platforms provide convenient ways to describe the typed signatures of components, e.g. like CORBA's IDL, they offer a quite low-level support to describe the concurrent behaviour of component. The ability to describe and verify the concurrent behaviour of interacting components is key aspect In the development of large component-based software system. This study propose a component interface specification using process algebra and configuration's role which allows one to prove correctness of software architecture generated at design level as well as to define compatibility relations by our evolution rule and $\pi$-graph. Also, we shown on an appropriateness of a specification techniques and definitions proposed in this paper by case-study.

• Journal of Korea Game Society
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• v.16 no.3
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• pp.65-76
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• 2016

The paradigm of the human experience through computer as a medium is moving from cultural interface to cultural software. Mod represents this paradigm shift in digital game culture. Until now, Digital game play focused on the immersive agency in the process of achieving the goals of the game. On the other hand, In Mod, play focus on generative agency in the process of creating and solving problems in game world. Through Mod, original game perceived as transformable data and creative material. Transformation and generation of such a game content through the user's Mod presents a sustainable model of the digital game.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.285-292
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• 2013

The method of recent information retrieval passes into an semantic search to provide more accurate results than keyword-based search. But in common user case, they are still accustomed to using existing keyword-based search. Hence they are hard to create a typed structured query language. In this paper, we propose to ontology knowledge-base scheme for query interpretation of these user. The proposed scheme was designed based on the OWL-DL for description logic reasoning, it can provide a richer representation of the relationship between the object by using SWRL(Semantic Web Rule Language). Finally, we are describe the experimental results of the similarity measurement for verification of a user query semantic interpretation.