• 한국CDE학회논문집
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• 제5권4호
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• pp.319-326
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• 2000

Expert systems using uncertain and ambiguous knowledge are not of the recent interests about uncertainty problem for performing inference similar to the decision making of a human expert. Human factors on rule-based systems often involve uncertain information. Expert systems had been used the methods of conflict resolution in a rule conflict situation, but this methods not properly solved the rule conflict. If a human expert appends a new rule to an original rule base, the rule base rightly causes a rule conflict. In this paper, the problem of rule conflict is regarded as one in which uncertainty of information is fundamentally involved. In the reduction of problem with uncertainty, we propose an enhanced rule ordering method, which improve the rule ordering method using Dempster-Shafer theory. We also propose a combinative index, which involve human factors of experts decision making.

• 지능정보연구
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• 제9권1호
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• pp.251-267
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• 2003

객체지향 데이터 베이스에서는 지능 정보시스템에서 요구하는 것을 만족하기 위하여 보다 지능적인 질의 처리 기법이 필요하다. 본 논문에서는 추론적 기법을 사용하여, 객체지향 데이터베이스에서의 지능적인 질의 처리하는 방법에 대하여 논의한다. 논문에서 제시하는 방법을 사용하여, 객체지향 데이터베이스에서 주어진 질의에 대한 답을 추상적으로 표현하는 지능적인 답을 얻을 수 있다. 본 논문에서 제안하는 지능적인 질의 처리 방법은 규칙 표현, 규칙 재편성, 전 분석, 분석의 네 단계로 구성된다. 규칙 표현 단계에서는 객체지향 데이터베이스 스키마를 사용하여 추론 규칙을 생성한다. 규칙 재편성 단계에서는 규칙에서 순환을 제거한다. 전 분석 단계에서는 유일한 내포적 문자를 얻기 위하여 규칙변환이 이루어진다. 분석 단계에서는 SLD-분석을 사용하여 내포적 답을 구한다.

• ETRI Journal
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• 제39권5호
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• pp.652-661
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• 2017

A mention has a noun or noun phrase as its head and constructs a chunk that defines any meaning, including a modifier. Mention detection refers to the extraction of mentions from a document. In mentions, coreference resolution refers to determining any mentions that have the same meaning. Pointer networks, which are models based on a recurrent neural network encoder-decoder, outputs a list of elements corresponding to an input sequence. In this paper, we propose mention detection using pointer networks. This approach can solve the problem of overlapped mention detection, which cannot be solved by a sequence labeling approach. The experimental results show that the performance of the proposed mention detection approach is F1 of 80.75%, which is 8% higher than rule-based mention detection, and the performance of the coreference resolution has a CoNLL F1 of 56.67% (mention boundary), which is 7.68% higher than coreference resolution using rule-based mention detection.

• ETRI Journal
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• 제38권6호
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• pp.1207-1217
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• 2016

The general method of machine learning has encountered disadvantages in terms of the significant amount of time and effort required for feature extraction and engineering in natural language processing. However, in recent years, these disadvantages have been solved using deep learning. In this paper, we propose a mention pair (MP) model using deep learning, and a system that combines both rule-based and deep learning-based systems using a guided MP as a coreference resolution, which is an information extraction technique. Our experiment results confirm that the proposed deep-learning based coreference resolution system achieves a better level of performance than rule- and statistics-based systems applied separately

• 산업공학
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• 제23권1호
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• pp.24-34
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• 2010

In the telecommunication system which is based on the existing PSTN(public switched telephone network), feature interaction has been an important research issue in order to provide seamless services to users. Recently, rapid proliferation of IP-based network and the various types of IP media supply services, the feature interaction from the perspective of application services has become a significant aspect. This paper presents conflict detection and resolution algorithms for designing and operating a variety of services that are provided through IP-based network. The algorithms use explicit service interactions to detect conflicts between a new service and registered services. They then apply various rules to reduce search space in resolving conflicts. The algorithms are applied to a wide range of realistic service provision scenarios to validate that it can detect conflicts between services and resolve in accordance with different rule sets. By applying the algorithms to various scenarios, it is observed that the proposed algorithms can be effectively used in operating an IP-based services network.

• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2000년도 한국우주과학회보 제9권1호
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• pp.34-34
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• 2000

No Abstract, See Full Text

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2002년도 춘계학술발표논문집
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• pp.106-108
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• 2002

반도체 physical layout design rule이 작아짐에 따라 Proximity effect와 overlay가 Pattern 구현에 크게 영향을 미치고 있다. Metal layer와 contact의 부족한 overlay margin으로 overlay 불량이 발생하고, 감소한 space margin으로 인해 bridge와 같은 문제가 나타난다. 따라서, resolution을 향상시키고, 최소한의 overlay margin을 확보함으로써 미세 pattern의 구현을 가능하게 한다. 이를 위해 OPC와 attPSM 같은 분해능향상기술이 사용된다. 그러나 attPSM의 사용은 원하지 않는 pattern이 생성되는 sidelobe와 같은 문제가 발생한다. 따라서 serial image simulation올 통해 추출한 rule을 rule-based correction에 적용하여 sidelobe현상을 방지한다. 그리고 overlay margin 부족으로 나타나는 문제는 metal layer와 contact overlap되는 영역의 line edge를 확장하고, rule checking을 통해 최소한의 space margin을 확보하여 해결한다 따라서 overlay error를 rule-based correction을 사용하여 효과적으로 방지한다.

• Journal of information and communication convergence engineering
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• 제14권2호
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• pp.97-105
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• 2016

With the increasing demand for interoperability among existing learning resource systems in order to enable the sharing of learning resources, such resources need to be annotated with ontologies that use different metadata standards. These different ontologies must be reconciled through ontology mediation, so as to cope with information heterogeneity problems, such as semantic and structural conflicts. In this paper, we propose an ontology-mapping technique using Semantic Web Rule Language (SWRL) to generate semantic mapping rules that integrate learning resources from different systems and that cope with semantic and structural conflicts. Reasoning rules are defined to support a semantic search for heterogeneous learning resources, which are deduced by rule-based inference. Experimental results demonstrate that the proposed approach enables the integration of learning resources originating from multiple sources and helps users to search across heterogeneous learning resource systems.

• 한국국방경영분석학회지
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• 제24권1호
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• pp.68-87
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• 1998

Techniques from decision analysis and expert system have both been extensively used in the development of computerized decision aids, although each discipline uses different approaches in knowledge (information or input) acquisition, representation, and problem solving methodology. From the perspective of many types of practical decision aiding applications, both normative decision aids and expert system technology have significant limitations. Many research efforts have been exerted toward complementing the one's deficiency with the other's possible techniques or vice versa. In this paper, among many possible complementary techniques for better decision aiding between decision analysis and expert system, we focus on the using prescriptive methodology of decision analysis which incorporates user's preference knowledge for conflict resolution in rule based expert system.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.116-119
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• 2005

As to the synthetical estimation of land covering parameters or the compounded land covering classification for multi-resolution satellite data, former researches mainly adopted linear or nonlinear regression models to describe the regression relationship of land covering parameters caused by the degradation of spatial resolution, in order to improve the retrieval accuracy of global land covering parameters based on 1;he lower resolution satellite data. However, these methods can't authentically represent the complementary characteristics of spatial resolutions among different satellite data at arithmetic level. To resolve the problem above, a new compounded land covering classification method at arithmetic level for multi-resolution satellite data is proposed in this .paper. Firstly, on the basis of unsupervised clustering analysis of the higher resolution satellite data, the likelihood distribution scatterplot of each cover type is obtained according to multiple-to-single spatial correspondence between the higher and lower resolution satellite data in some local test regions, then Parzen window approach is adopted to derive the real likelihood functions from the scatterplots, and finally the likelihood functions are extended from the local test regions to the full covering area of the lower resolution satellite data and the global covering area of the lower resolution satellite is classified under the maximum likelihood rule. Some experimental results indicate that this proposed compounded method can improve the classification accuracy of large-scale lower resolution satellite data with the support of some local-area higher resolution satellite data.