• Journal of Intelligence and Information Systems
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• 제9권3호
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• pp.49-63
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• 2003

This paper proposes and implements a tool for the development of efficient and reliable expert system. In the expert system the inference is executed, based on the knowledges stored in the knowledge base of specific domain. To acquire the reliable results of inference, the expert system requires the facilities which can access the various kinds of knowledge and maintain the consistency and accuracy of knowledge. In this context this paper implemented the knowledge management system which maintains the consistency and accuracy of knowledge, adding selectively the knowledges without error to the knowledge base by verifying their error before the knowledges are added to the knowledge base. At the same time this paper made the expert system call and use the procedural knowledge and the declarative knowledge in the data base so that it might use the various kinds of knowledge in the process of inference.

• Journal of Intelligence and Information Systems
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• 제7권2호
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• pp.65-81
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• 2001

This paper presets the process of knowledge aquisition by partitioning the phase of analysis & design for knowledge-base module construction of Expert System into five steps to derive rule systematically. Also, this paper presents the process and the task that knowledge engineer must do work each step. The knowledge-base module of STAFS expert system was constructed by considering the destruction rate and the commander\`s intention using the proposed rule derivation methodology.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.315-320
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• 1997

Rule minimization technique adapted from rough set theory was applied to remove redundant knowledge which is not necessary to make a knowledge base. New algorithm to diagnose fault using Improved Fuzzy Cognitive Maps(I-FCMs), and Fuzzy Associative Memory(FAM) is proposed. I-FCM[22] is superior to gathering knowledge from many experts and descries dynamic behaviors of systems very well. I-FCM is not only a knowledge base, but also a inference engine. FAM has learning capability like neural network[12]. Rule minimization and composition of I-FCM and FAM make it possible to construct compact knowledge base and breaks the border between inference engine and knowledge base.

• Journal of the Korea Society of Computer and Information
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• 제26권11호
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• pp.33-40
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• 2021

Due to advanced complex strategies, the complexity of information that a commander must analyze is increasing. An intelligent service that can analyze battlefield is needed for the commander's timely judgment. This service consists of extracting knowledge from battlefield information, building a knowledge base, and analyzing the battlefield information from the knowledge base. This paper extract information similar to an input query by embedding the knowledge base built in the 2^nd step. The transformation model is needed to generate the embedded knowledge base and uses the random-walk algorithm. The transformed information is embedding using Word2Vec, and Similar information is extracted through cosine similarity. In this paper, 980 sentences are generated from the open knowledge base and embedded as a 100-dimensional vector and it was confirmed that similar entities were extracted through cosine similarity.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.129-132
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• 1996

In this paper, we suggest a framework to represent the fuzziness in knowledge base as a perspective of the object-oriented paradigm. We divide the knowledge base in two parts. One is the object-base that stores the fuzzy propositions and the explanatory databases. The other is the rule-base that manages the rules between the fuzzy propositions. As the first step, we have to develop a new fuzzy object model that gives an easy way to represent the fuzzy propositions, that is, the fuzzy knowledge in the real world.

• Journal of the Korean Data and Information Science Society
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• 제8권2호
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• pp.173-181
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• 1997

In oriental medicine, it is required that correct medical knowledge should be maintained for medical expert system which analyzes and diagnoses patients symptoms. Typical medical expert system has a knowledge base as its core, and the knowledge base contains a domain specific knowledge about patients records. However, oriental medicine diagnostic knowledge is formed mostly as qualitative data, knowledge could be ambiguous and uncertain. In this paper, we looked at quantification methods and propose a method for quantifying the oriental medicine diagnostic knowledge, which is improving the knowledge base of an oriental medicine expert system.

• Journal of Korea Technology Innovation Society
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• 제5권1호
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• pp.72-89
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• 2002

This paper is based on a belief that, it is the simplest and best way measuring intangibles and knowledge assets on a monetary base, although there are many efforts to measure it. We analysis and compare with accounting, appraisal and valuation standards on Korean, USA and global level each. We conclude that valuation is appropriate for intangibles and knowledge assets, but we should check the standards of valuation on a social base in Korea.

• Journal of KIISE
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• 제42권12호
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• pp.1568-1574
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• 2015

Relation extraction plays a role in for the process of transforming a sentence into a form of knowledge base. In this paper, we focus on predicates in a sentence and aim to identify the relevant knowledge base properties required to elucidate the relationship between entities, which enables a computer to understand the meaning of a sentence more clearly. Distant Supervision is a well-known approach for relation extraction, and it performs lexicalization tasks for knowledge base properties by generating a large amount of labeled data automatically. In other words, the predicate in a sentence will be linked or mapped to the possible properties which are defined by some ontologies in the knowledge base. This lexical and ontological linking of information provides us with a way of generating structured information and a basis for enrichment of the knowledge base.

• Proceedings of the Korean Nuclear Society Conference
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• 한국원자력학회 1997년도 춘계학술발표회논문집(1)
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• pp.133-138
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• 1997

For a long time, a number of alarm processing techniques have been researched to reduce the number of actuated alarms for operators to deal with effectively during the abnormal as well as the normal conditions. However, the strategy that the only systems with a few clear technologies should be used as a part of an alarm annunciation system has been adopted considering the effectiveness and the reliability in actual alarm processing systems. Therefore, alarm processing systems have difficult knowledge-base maintenance problems and limited expansion or enhancement defects. To solve these shortcomings, the integrated knowledge-base which can express the general information related to all the alarm processing techniques is proposed and its management tool, Knowledge Input Tool for Alarm (KIT-A) which can handle the data of the knowledge-base efficiently is developed. Since the integrated knowledge-base with KIT-A can manipulate all the alarm information without the modification of alarm processing system itself, it is expected to considerably advance the overall capability of maintenance and enhancement of the alarm processing systems.

• Journal of Digital Convergence
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• 제12권6호
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• pp.245-252
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• 2014

Semantic search promises to provide more accurate result than present-day keyword matching-based search by using the knowledge base represented logically. But, the ordinary users don't know well the complex formal query language and schema of the knowledge base. So, the system should interpret the meaning of user's keywords. In this paper, we describe a user query interpretation system for the semantic retrieval of multimedia contents. Our system is ontological knowledge base-driven in the sense that the interpretation process is integrated into a unified structure around a knowledge base, which is built on domain ontologies.