• Annual Conference on Human and Language Technology
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• 1998.10c
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• pp.295-303
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• 1998

이 논문은 한국어와 일본어의 대역문형사전 구축 시에 동사의 대역어 선정을 위한 구체적인 방법을 실증적으로 제시하는데 목적이 있다. 현재 자연언어 처리에서의 동사의 의미기술은 동사의 중의성(重義性)을 해소하려는데 초점이 맞추어져 있다. 그 주된 방법론은 동사와 결합하는 명사 의미속성의 기술에 의해 중의성을 해소하려는 것이다. 이 논문에서는 개별언어에 있어서의 명사의 의미속성의 분류가 다국어를 대상으로 하는 경우 어떻게 다루어져야 하는가에 대해 언어학적인 조명을 하는데 목적이 있다. 아울러 현재까지 일본에서 구축된 동사의 의미사전 들을 비교, 명사 의미속성 분류의 기준이 어떻게 설정되어야 하는가에 대해 검증한다. 특히 외국어와의 대조는 동사와 명사의 공기관계가 각 언어마다 독특한 결합관계를 갖으며 문법체계의 차이로 인해 개별언어를 대상으로 했을 때보다 의미기술의 양상이 상당히 달라짐을 보여줄 것이다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.304-306
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• 2013

선박의 대형화, 고속화로 인한 해난 사고 증가에 대응하기 위해 전자해도 도입이 되었다. 전자해도는 속성정보와 공간정보로 구성되는 안전을 위한 GIS 데이터다. 전자해도 객체는 200여 가지로 각 객체별 다양한 속성으로 구성된다. 국제수로기구는 전자해도 객체에 포함되는 속성값 입력을 표준적으로 수행하기 위해 전자해도 객체 입력 지침(Use of Object Catalogue)를 정의 하였다. 전자해도 제작을 위해서 전자해도 객체지침서 교육이 필요하며, 교육 시에는 UOC가 사용되었다. 한편, UOC의 교육 효율성을 높이기 위해서 많은 요구사항이 제안 되었다. 본 연구에서는 UOC의 교육 효율성을 높이기 위해 지원 도구를 설계 및 개발 하였다.

• Journal of Radiation Protection and Research
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• v.18 no.1
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• pp.71-82
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• 1993

It is a fundamental element of the nuclear power plant operation to assess exactly the occupational radiation exposure. And, according to recently published ICRP 60 recommendation, it is needed to reduce individual radiaton exposure limit further. In this paper, an optimization techique was suggested for selection of alternatives for reducing occupational radiation exposure, and used in reviewing alternatives given by a plant utility. After the basic analysis, sensitivity analysis was performed to consider the variabilities of the economic variables. From the result, it was found that an option using steam generator nozzle dam and torquing machine was the best with respect to total benefits, and in case of multi-attribute utility analysis, an option using Co-No seal had the highest utility. Therefore, it was necessary to apply more than one technique togeter in optimization study and to consider qualitative factor, too.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.185-191
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• 2004

The mean and Clustering are important methods of data mining, which is now widely applied to various multi-attributes problem However, feature weighting and feature selection are important in those methods bemuse features may differ in importance and such differences need to be considered in data mining with various multiful-attributes problem. In addition, in the event of arithmetic mean, which is inadequate to figure out the most fitted result for structure of evaluation with attributes that there are weighted and ranked. Moreover, it is hard to catch hold of a specific character for assume the form of user's group. In this paper. we propose a dispersion mean algorithm for evaluation of similarity measure based on the geometrical figure. In addition, it is applied to mean classified by user's group. One of the key issues to be considered in evaluation of the similarity measure is how to achieve objectiveness that it is not change over an item ranking in evaluation process.

• Environmental and Resource Economics Review
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• v.12 no.3
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• pp.487-513
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• 2003

Currently, development of environmental index has been an increasingly important issue to achieve sustainable development, providing critical information to policy-makers. In particular, marine environmental composite index for Korea is widely required to establish. This paper constructs a marine environmental composite index using the OECD pressure-state-response (PSR) framework and employing multi-attribute utility theory (MAUT). The PSR framework links human activities as a pressure to environmental state and policy response. Weights are calculated by the MAUT technique. The paper provides annual pressure, state, response indices, and state index by sea area from 1991 to 2001 in Korea. The implications of the results and application plan of the index are also discussed.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.59-72
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• 2021

Concepts and categories offer the basis for inference pertaining to unobserved features. Prior research on category-based induction that used blank properties has suggested that similarity between categories and features explains feature inference (Rips, 1975; Osherson et al., 1990). However, it was shown by later research that prior knowledge had a large influence on category-based inference and cases were reported where similarity effects completely disappeared. Thus, this study tested category-based feature inference when features are connected in a causal chain and proposed a feature inference model that predicts participants' inference ratings. Each participant learned a category with four features connected in a causal chain and then performed feature inference tasks for an unobserved feature in various exemplars of the category. The results revealed nonindependence, that is, the features not only linked directly to the target feature but also to those screened-off by other feature nodes and affected feature inference (a violation of the causal Markov condition). Feature inference model of causal model theory (Sloman, 2005) explained nonindependence by predicting the effects of directly linked features and indirectly related features. Indirect features equally affected participants' inference regardless of causal distance, and the model predicted smaller effects regarding causally distant features.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.91-93
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• 2004

B2B Marketplace상에서의 거래에서 나타나는 주요한 특징은 다품종 및 대량의 물품 거래가 n：n거래 관계에 놓여있다는 점과 거래자가 원활한 거래 및 기업 내 관리를 위해 각자의 전자 카탈로그를 이용한 거래를 원한다는 정이다. 하지만 개별적인 전자 카탈로그 사용과 미흡한 표준안은 전자 카탈로그 상호 연계의 걸림돌이 되어 시장 형성의 걸림돌이 되고 있다. B2B Marketplace는 표준 분류체계를 중심으로 거래 대상 상품을 재분류하여 구매 당사자간의 거래 대상 물품에 대한 상호 애핑을 지원하는 방법 등으로 이를 충족시키려 하고 있다. 하지만 요청되는 다량의 물품에 대해 매번 분류를 수행해야 하는 고비용의 작업이라는 문제점이 있다. 본 논문에서는 이를 극복하기 위하여 기계학습 기법을 이용한 전자 카탈로그 상품 자동분류기를 모델링하고 이를 구현하는 것에 초점을 두었다. 상품의 속성별로 분류에 끼치는 영향력이 다론 것이라는데 착안하여 전자 카탈로그를 상품 단위로 재 모델링 하였으며 속성별 정보가 풍부하지 못한 정물 극복하기 위하여 속성값을 어휘 단위로 구분한 데이터를 추가 하는 확장 모델을 정의하였다. 또한 해당 모델을 학습시키기 위한 알고리즘으로는 속성별로 다른 가중치를 부여 할 수 있도록 확장된 Naive Bayesian Classifier를 고안하였다. 그리고 이론 B2B Market Place상의 실 데이터에 적용하여 고안된 모델의 유효성을 검증하였다.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.492-499
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• 2009

This research was conducted in order to know how influential the acknowledgment of factors such as the quality of educational contents and the conducting of off-line lectures is in terms of effective learning for leaners. Based on the satisfaction-importance model of the multi-attribute attitude model, this study would like to clarify the degree to which the quality of on-line contents of on-line education and the simultaneous conducting of off-line lectures influences one's learning attitude. On-line contents satisfaction will evaluated through the three categories: audio lectures, video lecture and WEI lectures, which make up the quality of on-line contents. We would also like to do a survey on the transformation of learning attitudes when on-line and off-line lectures were conducted simultaneously.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.373-377
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• 2009

This research was conducted in order to know how influential the acknowledgment of factors such as the quality of educational contents and the conducting of off-line lectures is in terms of effective learning for leaners. Based on the satisfaction-importance model of the multi-attribute attitude model, this study would like to clarify the degree to which the quality of on-line contents of on-line education and the simultaneous conducting of off-line lectures influences one's learning attitude. On-line contents satisfaction will evaluated through the three categories: audio lectures, video lecture and WBI lectures, which make up the quality of on-line contents. We would also like to do a survey on the transformation of learning attitudes when on-line and off-line lectures were conducted simultaneously.

• Journal of Information Technology Applications and Management
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• v.16 no.4
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• pp.93-107
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• 2009

This study investigated consumer preferences for Internet medical information service in China using the multi-attribute utility theory. The multi-attribute utility theory is a compositional approach for modeling consumer preferences wherein researchers calculate the overall service utility by summing up the evaluation results for each attribute. We found that Chinese Internet medical information users consider the availability of information and quick response to be the most important attributes. Further, they think that the comment feature is less important as compared to other attributes such as costs and updates. In addition, we found that the Internet users having more Internet experience consider these attributes to be more important as compared to the people who are just beginning to surf the Internet. For any successful Internet business, Internet marketers should assess individual-level preference and accordingly organize a fresh campaign. As of now, Internet marketers need estimation methods to predict the market performance of new services in many different business environments. We believe that the multi-attribute utility theory is a useful approach in this regard.