• 제목/요약/키워드: Knowledge-based System

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Organizational Knowledge Acquisition: A Fuzzy GSS Framework (조직의 지식 획득: 퍼지 GSS 프레임웍)

  • 이재남
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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    • pp.111-120
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    • 1999
  • Although the concept of viewing knowledge as a critical resource has been widely accepted in prior studies, it is not fully understood how to acquire available knowledge in order to improve organizational effectiveness. However, it si sure that organizational knowledge management should pursuit the achievement of the business goal by delivering relevant and useful information to the right person at the right time. Group Support System (GSS) can play an important role to transfer scatter information into meaningful business knowledge for supporting strategic corporate decision-making. This study proposes a fuzzy GSS framework for acquiring workgroup knowledge from individual memory and aggregating workgroup knowledge to organizational knowledge. This study also proposes an architecture to support the fuzzy GSS framework. The architecture consists of user agents, information management agents, and a fuzzy model manager. To illustrate how the fuzzy GSS framework can be used to support the whole process of organization knowledge acquisition, an Internet-based GSS was developed and applied in a marketing decision process. It showed that the framework was effective for acquiring organizational knowledge.

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BETTER INPUTS FOR KNOWLEDGE MANAGEMENT INFORMATION SYSTEMS: KNOWLEDGE SHARING MODELING AND THE INCENTIVES SYSTEM DESIGN

  • S. Ping Ho;Yaowen Hsu;Szu-Wei Lo
    • International conference on construction engineering and project management
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    • The 1th International Conference on Construction Engineering and Project Management
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    • pp.564-568
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    • 2005
  • Recently, Knowledge Management (KM) has been applied to construction industry. Surprising, there is few studies that address the most fundamental problem in KM: people may prefer not to share their knowledge so as to preserve their intellectual or unique values in the organization. Without the premise of each individual's willingness to share knowledge, there will be no valuable input for the IT system and, thus, no knowledge management at all. This paper aims to model the behavioral dynamics of knowledge sharing and to design an incentive system that may facilitate knowledge sharing for construction companies. In this paper, a game-theory based model will be developed, and the framework for designing an incentive system will be proposed according to the model.

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A Hybrid Approach Using Case-based Reasoning and Fuzzy Logic for Corporate Bond Rating

  • Kim, Hyun-jung;Shin, Kyung-shik
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 한국지능정보시스템학회 2003년도 춘계학술대회
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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.

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Rule Extraction from Neural Networks : Enhancing the Explanation Capability

  • Park, Sang-Chan;Lam, Monica-S.;Gupta, Amit
    • Journal of Intelligence and Information Systems
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    • 제1권2호
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    • pp.57-71
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    • 1995
  • This paper presents a rule extraction algorithm RE to acquire explicit rules from trained neural networks. The validity of extracted rules has been confirmed using 6 different data sets. Based on experimental results, we conclude that extracted rules from RE predict more accurately and robustly than neural networks themselves and rules obtained from an inductive learning algorithm do. Rule extraction algorithm for neural networks are important for incorporating knowledge obtained from trained networks into knowledge based systems. In lieu of this, the proposed RE algorithm contributes to the trend toward developing hybrid and versatile knowledge-based system including expert systems and knowledge-based decision su, pp.rt systems.

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Web-based Knowledge Management Model for Mid-Term and Long- Term Nuclear R&D Using Web Knowledge DataBase (웹 지식 데이터베이스를 활용한 원자력 중장기 연구개발 웹 기반 지식관리 모델)

  • 정관성;한도희
    • The Journal of Society for e-Business Studies
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    • 제5권2호
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    • pp.143-150
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    • 2000
  • This paper presents a methodology how to utilize management of research scheduling plan, processing, and results using Web Knowledge Database System, which integrates research knowledge management model under the Research & Development Environment. The content of this paper consists of description on utilization of the Web Knowledge Database System, sharing of the Research Knowledge through design data review, communications, and management of research knowledge flow during the Research & Development Period.

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Study on Inference and Search for Development of Diagnostic Ontology in Oriental Medicine (한의진단 Ontology 구축을 위한 추론과 탐색에 관한 연구)

  • Park, Jong-Hyun
    • Journal of Physiology & Pathology in Korean Medicine
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    • 제23권4호
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    • pp.745-750
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    • 2009
  • The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.

A Study of Designing the Knowledge Base System for the Query Extension by Index File (색인파일 기반의 질의어 확장용 지식베이스 구축에 관한 연구)

  • Seo, Whee
    • Journal of Korean Library and Information Science Society
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    • 제40권2호
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    • pp.139-159
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    • 2009
  • This study is to develop knowledge base system for query extension to the user oriented information retrieval. This study has survey the theories of the concept-based information retrieval method and statistic based information retrieval method. In the construction method of knowledge base, the common hypothesis is that the emergence of related term is the frequency of simultaneous emergence of a set of documents. Using the subject index file algorithms and the 'and' operator of boolean logic based on this hypothesis, this study builds the knowledge base. In this research experiment, a subject of knowledge base is education. Using the book of the Introduction to Education, two experimental knowledge base systems is constructed by the different indexing method. One system has constructed by controlled language indexing method, and another system has constructed by natural language indexing method. The performance of two knowledge base system is evaluated.

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The Development of Knowledge-Based CBT System for Ensuring the Facility Safety (설비의 안전성 확보를 위한 지식베이스 CBT시스템 구축에 관한 연구)

  • 나승훈;김병석;강경식
    • Journal of the Korean Society of Safety
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    • 제10권3호
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    • pp.115-119
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    • 1995
  • The effectiveness of an ensuring the facility safety depends on the ability to train the worker efficiently and strategy of facility control. This requires the instructor's awareness of the worker's current knowledge, in the specific areas of the worker's lacks of knowledge, and preferred methods of training. This paper presents a development of knowledge based on CBT system which will reduce the role of instructor from the training loop and be used the high technological method such as computer animation technique.

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A Tool for Implementation of Expert System with Knowledge Management System (지식관리 시스템을 수반한 전문가 시스템 구축 도구)

  • 서의현
    • 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.

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