• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.137-140
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• 1996

In order to solve the specific problems in system, the implementing of knowledge base suitable to the system architecture has to be expressed and leads to the resoning of the new facts. Not only the simple knowledge based on the bivalent logic but also the representation and acqusition of knowledge related to vague and imprecise linguistic variable is necessary to the knowledge in the real world,i.e the knowledge of which facts and rules are composed. In this point of view, this survey implements the inference and retrieval of the fuzzy linguistic variables so that it can process the ambiguous information which appears the imprecision of the linguistic boundary.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.67-84
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• 2008

This paper proposes a design and realization for the semantic search system. The proposed model includes three Architecture Layers of a Semantic Search System ; (they are conceptually named as) the Knowledge Acquisition, the Knowledge Representation and the Knowledge Utilization. Each of these three Layers are designed to interactively work together, so as to maximize the users' information needs. The Knowledge Acquisition Layer includes index and storage of Semantic Metadata from various source of web contents(eg : text, image, multimedia and so on). The Knowledge Representation Layer includes the ontology schema and instance, through the process of semantic search by ontology based query expansion. Finally, the Knowledge Utilization Layer includes the users to search query intuitively, and get its results without the users'knowledge of semantic web language or ontology. So far as the design and the realization of the semantic search site is concerned, the proposedsemantic search system will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.184-204
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• 2015

Fuzzy Formal Concept Analysis (FCA) is a mathematical tool for the effective representation of imprecise and vague knowledge. However, with a large number of formal concepts from a fuzzy context, the task of knowledge representation becomes complex. Hence, knowledge reduction is an important issue in FCA with a fuzzy setting. The purpose of this current study is to address this issue by proposing a method that computes the corresponding crisp order for the fuzzy relation in a given fuzzy formal context. The obtained formal context using the proposed method provides a fewer number of concepts when compared to original fuzzy context. The resultant lattice structure is a reduced form of its corresponding fuzzy concept lattice and preserves the specialized and generalized concepts, as well as stability. This study also shows a step-by-step demonstration of the proposed method and its application.

• Journal of the Korean Society for information Management
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• v.7 no.2
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• pp.35-57
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• 1990

Knowledge-based system is interpreted from the viewpoint of library and information science, and the concept of knowledge is defined in relation to information and data. Knowledge representation techniques are illustrated with examples from intelligent information retrieval systems and expert systems developed in library and information science field.

• Journal of the Korean Society for information Management
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• v.16 no.4
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• pp.53-74
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• 1999

This paper describes concept mapping techniques for eliciting and representing knowledge. Concept mapping techniques range from very informal to very formal. Informal concept mapping techniques are usually very easy to use and understand for humans, but not for computers. Formal concept mapping techniques are computational, but humans usually find them hard to understand and use. A knowledge acquisition and representation tools which handle both kinds, and the transition from informal to formal, would be very useful. It is proposed that concept maps be regarded as basic components of any knowledge-based system, complementing text and image with formal and informl active diagrams.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.474-483
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• 2003

A number of studies for corporate bond rating classification problems have demonstrated that artificial intelligence approaches such as Case-based reasoning (CBR) can be alternative methodologies to statistical techniques. CBR is a problem solving technique in that the case specific knowledge of past experience is utilized to find a most similar solution to the new problems. To build a successful CBR system to deal with human information processing, the representation of knowledge of each attribute is an important key factor We propose a hybrid approach of using fuzzy sets that describe the approximate phenomena of the real world because it handles inexact knowledge represented by common linguistic terms in a similar way as human reasoning compared to the other existing techniques. Integration of fuzzy sets with CBR is important to develop effective methods for dealing with vague and incomplete knowledge to statistical represent using membership value of fuzzy sets in CBR.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.18.1-18
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• 2001

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.801-802
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• 2007

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.27-42
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• 1989

REA (Restricted Entity Aspect) model is a knowledge representation model to classify the aspect type, the EA model component, into five aspects (IS-A-aspect, A-PART-OF aspect, attribute aspect, role aspect, and operation aspect). EATPS, the knowledge representation system, consists of user interface module, knowledge creation module, instance management module, schema management module, and integrity checking module. EATPS creates and manages interactively REA model based knowledge base. This paper shows the structure and functions of EATPS, the design and interactive construction of the knowledge definition language EAKDL, the functions and algorithm of class creation module, and the functions and algorithm of instance creation module to include inheritance inference mechanism.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.157-185
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• 1998

One of the essential issues in model systems is how to represent and manipulate mathematical modeling knowledge. As the bases of integrated modeling environments, current modeling frameworks have limitations: lack of facility to coordinate different users perpectives and lack of mechanism to reuse modeling knowledge. In this paper, multi-facetted modeling approach is proposed as a basis for the development of integrated modeling environment which provides facilities for (1) independent management of modeling knowledge from individual models； (2) object-oriented conceptual blackboard concept； (3) multi-facetted modeling； and (4) declarative representation of mathematical knowledge. The proposed multi-facetted approach is illustrated using multicommodity transportation models.