• 로봇학회논문지
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• 제2권1호
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• pp.80-92
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• 2007

For the pervasive computing in ubiquitous environment, it is very important to manage the context model to provide pertinent context knowledge to context-aware applications. The context model should be able to support efficiently the context knowledge reusing and sharing as well as reasoning. Previous works focus mainly on the context knowledge representation scheme for reasoning. This paper proposes a context knowledge modeling scheme especially for reusing and sharing. This scheme provides well-established principles and guides for 1) context knowledge modularization and hierarchization, and for 2) context knowledge identification and organization. Once the context models are built according to the scheme, the structure of the context model and the meanings of the context knowledge elements become clear and consistent, so that context-aware applications can share and reuse the context knowledge in easy and error-reduced manner. This paper also discusses the implementation of a context model and an application for Presentation Helper scenario running on a software middleware system (CAMUS) for ubiquitous service robots which is being developed by ETRI Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권9호
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• pp.3211-3230
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• 2014

Recently, sparse coding has achieved remarkable success in image representation tasks. In practice, the performance of clustering can be significantly improved if limited label information is incorporated into sparse coding. To this end, in this paper, a novel semi-supervised algorithm, called constrained sparse concept coding (CSCC), is proposed for image representation. CSCC considers limited label information into graph embedding as additional hard constraints, and hence obtains embedding results that are consistent with label information and manifold structure information of the original data. Therefore, CSCC can provide a sparse representation which explicitly utilizes the prior knowledge of the data to improve the discriminative power in clustering. Besides, a kernelized version of our proposed CSCC, namely kernel constrained sparse concept coding (KCSCC), is developed to deal with nonlinear data, which leads to more effective clustering performance. The experimental evaluations on the MNIST, PIE and Yale image sets show the effectiveness of our proposed algorithms.

• 컴퓨터교육학회논문지
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• 제11권3호
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• pp.43-55
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• 2008

본 연구는 학습(learning)을 통해 습득된 추상적 형태의 암묵적인 지식(implicit knowledge)을 전달하거나 명시적인 형태로 재구성(reconstruction)할 때 지식을 어떤 방법으로 표현하거나 재구성해야 하는지, 그리고 어떤 표현 방법이 자신의 생각과 지식을 효과적으로 전달하는데 중요한 요소로 작용하는지에 대한 연구를 다룬다. 현재 대학과 같은 상위수준의 교육기관에서의 교육에서는 교수자가 전달하는 내용을 수업을 통하여 듣게 되고 학습을 통해 그 내용을 자신의 지식구조에 맞도록 습득해 가는 과정을 거친다. 이 과정에서 학습자는 자신이 학습을 통해 습득한 지식을 자신의 인지구조 (cognitive model)에 맞게 재구성하게 된다. 이러한 지식을 다시 전달할 때 어떤 방법을 쓰면 효과적으로 전달할 수 있을지 고민하게 되고 그 결과, 적절한 방법을 찾아 표현하게 된다. 본 연구는 이러한 과정을 실제적으로 실험해보고 자신이 재구성한 지식을 전달하는데 어떤 방법이 효과적이었는지, 또한 상대방의 지식이 어떻게 표현될 때 받아들여 이해하기 쉬운지를 자료에 대한 상호평가 분석을 통해 그 요소를 분석하였다. 본 연구는 효과적인 지식 전달 방법과 지식습득 평가에 활용할 수 있는 기초연구가 될 것이다.

• 한국정보처리학회논문지
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• 제5권8호
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• pp.2075-2082
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• 1998

규칙 기반 지식표현은 전문가 시스템의 지식을 저장하고 조작하는 기법중 가장 많이 사용되는 기법이다. 그런데 이 방법으로 표현된 지식의 양은 점점 많아지며, 그 관계가 복잡해지고 내용이 변경될 수 있기 때문에 지식베이스의 일관성 및 완결성을 유지하는 검증 시스템이 필요하다. 따라서 본 논문에서는 새로운 규칙이 첨가될 때 야기될 수 있는 오류를 구조적 측면과 의미론적 측면에서 검증한 후 자체 수정하거나 자체 수정이 불가능할 경우 전문가가 수정하도록 하여 일관성과 완결성이 확증된 후 새로운 규칙이 추가되어질 수 있도록 함으로써 전문가 시스템의 신뢰도를 높이고 효율성을 제고할 수 있는 검증시스탬이 제안되었다.

• 한국콘텐츠학회논문지
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• 제12권6호
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• pp.21-31
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• 2012

가상현실은 현실처럼 구성된 가상공간과 그 속에서 살아가는 에이전트들로 구성되어 있다. 여기서 가상공간이란 시각적 표현뿐만 아니라 질량, 중력, 마찰력등과 같은 물리속성들과 법칙들에 의해 규율되는 질서 있는 공간을 의미한다. 이러한 가상공간을 구축하기 위해서는 인간과 유사한 행동을 하는 가상 에이전트와 그를 둘러싼 환경을 설계해야 한다. 정해진 공간이나 기억에 대하여 설계자의 지식에 따라서 그대로 반응하게 만들어진 기존의 반응형 에이전트의 행동방식을 개선하여 능동적 행동이 가능하기 위해서는 에이전트의 활동 공간에 관련된 다양한 지식이 필요하다. 본 연구에서는 이러한 지식중에서 공간적 지식에 관한 표현구조를 설계하고 구현한다. 이와 같은 지식표현은 사실적이고 효율적인 물리적 가상환경을 구축하는 바탕으로 사용됨과 동시에 가상에이전트들의 지식을 표현하는 구조로 이용된다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.410-420
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• 2001

A primitive conceptualization is defined as the set of all intended situations. A non-primitive conceptualization is defined as the set of all the pairs every of which consists of an intended knowledge system and the set of all the situations admitted by the knowledge system. The reality of a domain is considered as the set of all the situation which have ever taken place in the past, are taking place now and will take place in the future. A conceptualization is defined as precise if the set of intended situations is equal to the domain reality. The representation of various elements of a domain ontology in a model of the ontology is considered. These elements are terms for situation description and situations themselves, terms for knowledge description and knowledge systems themselves, mathematical terms and constructions, auxiliary terms and ontological agreements. It has been shown that any ontology representing a conceptualization has to be non-primitive if either (1) a conceptualization contains intended situations of different structures, or (2) a conceptualization contains concepts designated by terms for knowledge description, or (3) a conceptualization contains concept classes and determines properties of the concepts belonging to these classes, but the concepts themselves are introduced by domain knowledge, or (4) some restrictions on meanings of terms for situation description in a conceptualization depend on the meaning of terms for knowledge description.

• 한국지능시스템학회논문지
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• 제17권2호
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• pp.276-283
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• 2007

It has been shown that the structure identification of a neuro-fuzzy model improves their accuracy performances in a various modeling problems. In this paper, we claim that the structure identification of a neuro-fuzzy model can also reduce the degree of inconsistency of its fuzzy rulebase. Thus, the resulting neuro-fuzzy model serves as more like a structured knowledge representation scheme. For this, we briefly review a structure identification method of a neuro-fuzzy model and propose a systematic method to measure inconsistency of a fuzzy rulebase. The proposed method is applied to problems or fuzzy system reproduction and nonlinear system modeling in order to validate our claim.

• 한국실내디자인학회논문집
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• 제11호
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• pp.70-73
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• 1997

This paper explores ways to develop efficient methods to construct the web-based interior design database based on hypermedia technology. First the role of hypermedia in design was investigated. We propose the structure of knowledge representation for interior design works. Also, we discuss how a design case can be retrieved from the design database. This paper also identified further research issues such as design case retrieval from numerous design cases and components of the virtual design studio.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.435-441
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• 2008

Building Information Modelings(BIM) are more complex than typically required for early phase of the design process of a building. Construction projects have many participants from various disciplines involved throughout the entire process. Therefore the success of the project greatly depend on the efficiency of decision-making using the information generated from each process stage. This research utilized an ontology to provide an underlying structure of objects and relationships of a building. The OWL is introduced as a main vehicle to encode the information and knowledge about the building structures and spaces. A case study was conducted to develop a structured representation of an ontology where the relationships among the necessary components in the stage of preliminary design were to be automatically utilized to plan on the sizes of each room in a building and structured thoroughly with a simple structured representation.

• 한국경영과학회지
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• 제24권1호
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• pp.99-117
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• 1999

Since query language is used as a handy tool to obtain information from a database, a more intelligent query answering system is needed to provide user-friendly and fault-tolerant human-machine Interface. Frequently, database users prefer less rigid querying structure, one which allows for vagueness in composing queries, and want the system to understand the intent behind a query. When there is no matching data available, users would rather receive approximate answers than a null information response. This paper presents a knowledge abstraction database that facilitates the development of such a fault-tolerant and intelligent database system. The proposed knowledge abstraction database adepts a multilevel knowledge representation scheme called the knowledge abstraction hierarchy(KAH), extracts semantic data relationships from the underlying database, and provides query transformation mechanisms using query generalization and specialization steps. In cooperation with the underlying database, the knowledge abstraction database accepts vague queries and allows users to pose approximate queries as well as conceptually abstract queries. Specifically. four types of vague queries are discussed, including approximate selection, approximate join, conceptual selection, and conceptual Join. A prototype system has been implemented at KAIST and is being tested with a personnel database system to demonstrate the usefulness and practicality of the knowledge abstraction database in ordinary database application systems.