• Korean Journal of Computational Design and Engineering
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• v.10 no.1
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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.

• Knowledge Management Research
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• v.16 no.4
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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.

• Knowledge Management Research
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• v.4 no.2
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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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• v.17 no.11
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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.

• Proceedings of the IEEK Conference
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• 2002.07b
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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.

• Knowledge Management Research
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• v.7 no.2
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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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.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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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.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.99-106
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• 2014

Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.

• Informatization Policy
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• v.20 no.4
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• pp.23-50
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• 2013

The main purpose of this study is to empirically examine and to develop the optimal model about an influential relationship between the types of source-based trust and knowledge sharing of local government officials. Procedural and distributive justice-based calculative trust in organization, cognition-based trust in organization, cognition-based trust in supervisor, cognition-based trust in coworkers, and emotion-based trust in coworkers were set up as independent variables of this research model, and sharing of tacit knowledge and explicit knowledge based on the knowledge content as dependent variables. The research results shows that the suitability of each model has approximate value to the required level, and that emotion-based trust in coworkers significantly affects knowledge sharing for both the individual and integrated factors in hypothetical influential relationship. This study is expected to help to enable knowledge sharing in various situations by dividing the concepts of trust that affect knowledge sharing into a few types, and deriving the influential model of knowledge sharing by types.