• 한국CDE학회논문집
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• 제10권1호
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• pp.49-60
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• 2005

Existing CAD systems have configured geometry data and it is necessary to extend the configured geometry into a knowledge-based system. An intelligent CAD system emerged to provide such a knowledge-based system. However the intelligent CAD system has a limited product model to represent various knowledge models. This paper presents a model, called extended intelligent CAD model, which can extend the product model of the intelligent CAD system into further detailed knowledge model. The extended intelligent CAD model includes a whole design process knowledge and an efficiency of the model has been verified via a knowledge based wiper design system. The model can improve the functionality and efficiency of the existing CAD systems.

• 지식경영연구
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• 제16권4호
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• pp.169-190
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• 2015

The status of small and medium-sized enterprises has been changed into more independent business entities rather than simply subcontractor so that the utilization of specialized knowledge has been much more necessary for the survival in the market. However, small and medium-sized enterprises, it is difficult to sufficient investment in knowledge services due to limited resources relative to large enterprises and demand for knowledge services business of government support is growing. For this reason, it is important to measure accurately the demand for knowledge services of small and medium-sized enterprises in knowledge management for effective utilization of knowledge service. In this study, we analyzed previous studies on small and medium-sized enterprises knowledge services that can be utilized in a comprehensive way. As a result, we developed knowledge service needs assessment model based on five critical success factors for continual growth and 12 types of knowledge service. This model has been modified and supplemented through expert meeting using delphi research method and topic modeling analysis using secondary data. This study is attempted to appropriately measure necessary knowledge services for small and medium-sized enterprises so that generated the evaluation model of knowledge service demands, comprehensively dealing with core knowledge services for many kinds of business entities. It is expected that the developed model will be a useful tool to understand and evaluate knowledge services demands of enterprises.

• 지식경영연구
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• 제4권2호
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• pp.35-53
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• 2003

In recent years, knowledge has emerged as a major source of competitive advantage due to the continuous development of information and communication technology, the acceleration of globalization, and the entry into knowledge-based society. Thus interests in knowledge management have been increased significantly. Nevertheless theoretical backgrounds of knowledge management are not actively discussed. Studies on the knowledge management of R&D groups initiating knowledge creation and sharing are not actively conducted either. This study, therfore, provides a research model of knowledge management to investigate relationships among resource and institutional characteristics, knowledge management activities, and knowledge management performance of R&D groups based on knowledge-based theories and institutionalization theories. This study further offers research propositions inherent in the model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.2903-2923
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• 2023

Knowledge recommendation is a type of recommendation system that recommends knowledge content to users in order to satisfy their needs. Although using graph neural networks to extract data features is an effective method for solving the recommendation problem, there is information loss when modeling real-world problems because an edge in a graph structure can only be associated with two nodes. Because one super-edge in the hypergraph structure can be connected with several nodes and the effectiveness of knowledge graph for knowledge expression, a dual-channel hypergraph convolutional neural network model (DCHC) based on hypergraph structure and knowledge graph is proposed. The model divides user data and knowledge data into user subhypergraph and knowledge subhypergraph, respectively, and extracts user data features by dual-channel hypergraph convolution and knowledge data features by combining with knowledge graph technology, and finally generates recommendation results based on the obtained user embedding and knowledge embedding. The performance of DCHC model is higher than the comparative model under AUC and F1 evaluation indicators, comparative experiments with the baseline also demonstrate the validity of DCHC model.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1165-1168
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• 2002

Knowledge acquisition is the process that extracts the required knowledge from available sources, such as experts, textbooks and databases, for incorporation into a knowledge-based system. Knowledge acquisition is described as the first step in building expert systems and a major bottleneck in the efficient development and application of effective knowledge based expert systems. One cause of the problem is that the process of human reasoning we need to understand for knowledge-based system development is not available for direct observation. Moreover, the expertise of interest is typically not reportable due to the compilation of knowledge which results from extensive practice in a domain of problem solving activity. This is also a problem of modeling knowledge, which has been described as not a problem of accessing and translating what is known, but the familiar scientific and engineering problem of formalizing models for the first time. And this formalization process is especially difficult for knowledge engineers who are often faced with the difficult task of creating a knowledge model of a domain unfamiliar to them. In this paper, we propose an automated knowledge acquisition tool which is based on an implementation of the Inferential Modeling Technique. The Inferential Modeling Technique is derived from the Inferential Model which is a domain-independent categorization of knowledge types and inferences ［Chan 1992］. The model can serve as a template of the types of knowledge in a knowledge model of any domain.

• 지식경영연구
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• 제7권2호
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• pp.53-68
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• 2006

Knowledge has become an important resource for organization. The manufacturing industry is usually operated on the basis of business processes, and most workers are familiar with their own processes. The process-based approach, therefore, can provide an efficient way to capture and navigate knowledge. In this study, we focus on knowledge which may be missed during knowledge transfer among workers. For this, we propose a method for analyzing knowledge flow, which is passed among business processes. We propose a process-based knowledge management framework for analyzing knowledge flow, which employs a two-phase analysis: process analysis and knowledge flow analysis. A knowledge flow model, represented by Knowledge Flow Diagram, is proposed as a tool for representing knowledge. We formulate several semantics for knowledge flow modeling. We build the three-level schema: conceptual, logical, and physical in order to automate the knowledge model adaptive to knowledge management systems. The proposed approach is verified and illustrated through a case study on the manufacturing process of A Company.

• 산업경영시스템학회지
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• 제31권2호
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• pp.1-10
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• 2008

In the knowledge-based society which recognizes knowledge as a core value, knowledge management is one of the most interesting issues. The creation of knowledge within an organization occurs as a result of interactions of tacit and explicit knowledge, in process of knowledge conversion. One useful model of this process is the SECI model which stands for a process of socialization, externalization, combination and internalization of knowledge. The enterprise competitive power depends on how an organization accelerates the speed of the cycle of knowledge creation well. In this paper we introduce a knowledge management promotion system based on SECI model and proposal system to promote the cycle of knowledge creation in production fields, and study an enterprise case.

• 지능정보연구
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• 제6권1호
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• pp.35-50
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• 2000

Diverse requirements of users on web-based model management force a system agent to develop user-adaptive building a model in reality and providing an adequate solution method of the model. The relationship between models is important knowledge for the agent to effectively build a new model to adaptively adjust an existing model under a problem and to efficiently connect the new model into an adequate solution method. Since the generating process of the inter-model relationship is more difficult than the building a new model however the process mostly depends on the knowledge of operation research experts. Without the adequate scheme of the inter-model relationship the burden of the management for the agent increases rapidly and the quality of the services may worsen. This study shows that meta-knowledge generated from relationship between models is important for the user to build a model in reality and to acquire the solver appropriate to the model. The relationship that consists of common and exclusive objects between models can be represented by frames. The system under development to implement the idea includes user-adaptive ability which identifies a model through forward chaining method and searches the solver appropriate to the model by using the meta knowledge. We illustrate the meta knowledge with an applied delivery system in supply chain management.

• 인터넷정보학회논문지
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• 제15권6호
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• pp.99-106
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• 2014

최근 자연어 및 정형언어 처리, 인공지능 알고리즘 등을 활용한 효율적인 의미 기반 지식모델의 생성과 분석 방법이 제시되고 있다. 이러한 의미 기반 지식모델은 효율적 의사결정트리(Decision Making Tree)와 특정 상황에 대한 체계적인 문제해결(Problem Solving) 경로 분석에 활용된다. 특히 다양한 복잡계 및 사회 연계망 분석에 있어 정적 지표 생성과 회귀 분석, 행위적 모델을 통한 추이분석, 거시예측을 지원하는 모의실험 모형의 기반이 된다. 하지만 대부분의 지식 모델은 특정 지표나 정제된 데이터를 수동적으로 모델링하여 분석에 활용한다. 본 논문에서는 텍스트 마이닝 기술을 통해 방대한 비정형 정보로부터 지식 모델을 구성하는 토픽인자와 관계 노드를 생성하고 이를 통합하는 방법과 정형적 알고리즘을 제시한다. 이를 위해 먼저, 텍스트 마이닝을 통해 도출되는 키워드 맵을 동치적 지식맵으로 변환하고 이를 의미적 지식모델로 통합하는 방법을 설명한다. 또한 키워드 맵으로부터 유의미한 토픽 맵을 투영하는 방법과 의미적 동치 모델을 유도하는 알고리즘을 제안한다.

• 정보화정책
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• 제20권4호
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• pp.23-50
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• 2013

이 연구는 공공조직 구성원의 신뢰기반에 따른 신뢰유형이 지식공유(암묵지식과 명시지식)에 미치는 영향관계를 경험적으로 살펴보고 최적모형을 도출하는데 목적을 두었다. 분석모형의 구성변수로는 신뢰기반에 따른 신뢰유형을 조직의 절차적 및 분배적 공정성에 기인한 타산적 신뢰, 조직과 상사 그리고 동료에 대한 인지적 신뢰, 동료에 대한 감성적 신뢰 요인 등을 독립변수로 설정하였으며, 종속변수로는 지식내용을 중심으로 암묵지식 공유와 명시지식 공유로 구분하였다. 분석 과정에서는 신뢰기반에 따른 신뢰유형과 지식공유를 구성하는 개별요인은 물론 이들 개별 요인들의 상위개념을 통합요인으로 구분하여 분석하였다. 분석결과 각 모형의 적합도는 요구수준에 근사하게 도달되었으며, 가설적 영향관계에서는 통합요인 및 개별요인 모두에서 '동료에 대한 감성적 신뢰'가 지식공유에 유의적 영향을 미치는 것으로 파악되었다. 연구결과의 정책적 함의로는 첫째, 지식공유에 영향을 미치는 신뢰 개념을 구체적으로 구분하여 유형화하고 유형별로 지식공유의 영향모형을 도출함으로써 상황에 적합한 지식공유 활성화 방안을 마련할 수 있는 토대를 제공했다는 점과 둘째, 지식공유를 암묵지식과 명시지식으로 구분함으로써 지식공유의 내용에 따른 차별화된 지식공유의 촉진 방안을 모색하는 토대를 제공했다는 점 등을 제시하였다.