• Knowledge Management Research
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• v.13 no.2
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• pp.1-18
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• 2012

This article describes how attributes of social network contribute to enhance innovativeness of corporation which is considered to be one of the competitive factors in this global market. The study especially focused on employees' formal and informal communication that is expected to play a mediating role between the factors. 211 employees were randomly selected to participate in an online survey. The result has shown that the static correlation exists between social network, communication, and innovativeness. Closeness of social network was the only influencing factor on communication and innovativeness, and had a partial mediated effect between social network and innovativeness. Based on the suggested contribution for HRD intervention, various communication channels should be developed and supported in order to enhance innovation among social networks in organizations.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.269-284
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• 2022

Exploring research similarity of researchers offers insight on research communities and potential interactions among scholars. While co-authorship is a popular measure for studying research similarity of researchers, it cannot provide insight on authors who have not collaborated yet. In this work, we present novel approach to capture research similarity of authors using citation information. Extensive study is conducted on DATA & KNOWLEDGE ENGINEERING (DKE) publications to demonstrate and compare suggested approach with co-authorship based approach. Analysis result shows that proposed approach distinguishes author relationships that is not shown in co-authorship network.

• Journal of Korea Multimedia Society
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• v.25 no.7
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• pp.895-902
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• 2022

Building segmentation using satellite imagery such as EO (Electro-Optical) and SAR (Synthetic-Aperture Radar) images are widely used due to their various uses. EO images have the advantage of having color information, and they are noise-free. In contrast, SAR images can identify the physical characteristics and geometrical information that the EO image cannot capture. This paper proposes a learning framework for efficient building segmentation that consists of a teacher-student-based privileged knowledge distillation and deformable convolution block. The teacher network utilizes EO and SAR images simultaneously to produce richer features and provide them to the student network, while the student network only uses EO images. To do this, we present objective functions that consist of Kullback-Leibler divergence loss and knowledge distillation loss. Furthermore, we introduce deformable convolution to avoid pixel-level noise and efficiently capture hard samples such as small and thin buildings at the global level. Experimental result shows that our method outperforms other methods and efficiently captures complex samples such as a small or narrow building. Moreover, Since our method can be applied to various methods.

• Knowledge Management Research
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• v.1 no.1
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• pp.81-90
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• 2000

This study proposes the knowledge discovery process for the effective mining of knowledge on the web. The proposed knowledge discovery process uses the Prior knowledge base and the Prior knowledge management system to reflect tacit knowledge in addition to explicit knowledge. The prior knowledge management system constructs the prior knowledge base using a fuzzy cognitive map, and defines information to be extracted from the web. In addition, it transforms the extracted information into the form being handled in mining process. Experiments using case-based reasoning and neural network" are performed to verify the usefulness of the proposed model. The experimental results are encouraging and prove the usefulness of the proposed model.

• Knowledge Management Research
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• v.1 no.1
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• pp.1-18
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• 2000

Knowledge management has recently emerged as an appealing subject in management literature. Although its history is short, it can benefit greatly from the long history of other related disciplines in building its theories. Innovation, organizational learning, knowledge creation, organizational capability building, technology transfer and network, information technology, organizational behavior, and intellectual capital are the disciplines that have accumulated theories related to knowledge management. This paper first presents a conceptual framework that integrates three dimensions: the characteristics of knowledge (tacit and explicit), knowledge process (acquisition, creation, diffusion, storing, measurement, and application of knowledge), and the unit of analysis (individual, organization, sector, and nation). The conceptual framework produces a number of cells that need to be filled by new theories in order to understand knowledge management better. It then reviews existing theories available in the related disciplines that may be used as building blocks in constructing new theories for these cells. Finally, based on the theories available in other disciplines, the paper suggests a set of future research directions for knowledge management at the level of individual, organization, sector, and nation.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.54-61
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. By using the FCM, authors have proposed FCM-based fault diagnostic algorithm. However, it can offer multiple interpretations for a single fault. In process engineering, as experience accumulated, some form of quantitative process knowledge is available. If this information can be integrated into the FCM-based fault diagnosis, the diagnostic resolution can be further improved. The purpose of this paper is to propose an enhanced FCM-based fault diagnostic scheme. Firstly, the membership function of fuzzy set theory is used to integrate quantitative knowledge into the FCM-based diagnostic scheme. Secondly, modified TAM recall procedure is proposed. Considering that the integration of quantitative knowledge into FCM-based diagnosis requires a great deal of engineering efforts, thirdly, an automated procedure for fusing the quantitative knowledge into FCM-based diagnosis is proposed by utilizing self-learning feature of neural network. Finally, the proposed diagnostic scheme has been tested by simulation on the two-tank system.

• Knowledge Management Research
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• v.16 no.1
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• pp.143-170
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• 2015

In the rapidly changing business environment, companies are introducing information technology to effectively manage internal resources in order to achieve a sustainable competitive advantage. We presented the Enterprise Social Network Service(SNS) as new information technology. Enterprise SNS provided employers with sociable functions like Facebook while supporting general task such as mail, authorization and notice. In this research, we focused on Enterprise SNS and suggested self-disclosure, enjoyment in helping others, perceived organizational support, generativity capacity as antecedent variables of Enterprise SNS usage. In addition, we verified the effect of the mediating role of generativity capacity between Enterprise SNS usage and job performance. For empirically verifying the proposed model, we collected sample data from 225 workers using Enterprise SNS and conducted analysis using a structural equation modeling. We expect that this study provides managers who are interested in introducing enterprise SNS with insights on how to facilitate enterprise SNS usage. Also, this study suggests useful theoretical implications to researchers who are interested in the use of enterprise SNS from the context of knowledge management.

• Knowledge Management Research
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• v.20 no.4
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• pp.23-38
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• 2019

The Korean government has been trying to create new economic value-added and jobs by the openness and utilization of open government data. However, most of open government data has poor utilization rate. Although open government data standardization is a major cause of those inactivation, it is not sufficient to conduct empirical research on open government data itself. Based on this trend, this paper aims to find the priority area for opening data and suggests a realistic directions of standardization of open government data. Text mining and social network analysis approaches are used to analyze open government data and standardization. This research suggests the guides to open government data managers in practical view from selection of data to standardization direction. In addition, this research has academic implications to the knowledge management systems in terms of suggesting standardization direction by using various techniques.

• Journal of the Korea Safety Management & Science
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• v.9 no.5
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• pp.79-85
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• 2007

Intelligent machines respond to external environments on the basis of decisions that are made by sensing the changes in the environment and analyzing the obtained information. This study focuses on the construction of a knowledge base which enables decision making with that information. Approximately 70% of all errors that occur in machine tools are caused by thermal error. In order to proactive deal with these errors, a system which measures the temperature of each part and predicts and compensates the displacement of each axis has been developed. The system was built in an open type controller to enable machine tools to measure temperature changes and compensate the displacement. The construction of a machining knowledge base is important for the implementation of intelligent machine tools, and is expected to be applicable to the network based intelligent machine tools which look set to appear sooner or later.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.117-120
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• 2013

스마트폰의 보급으로 모바일 소셜 네트워크 게임(SNG: Social Network Game)을 즐기는 사용자들이 증가하고 있다. 그러나, SNG의 특성에 맞는 자원 활용률을 고려한 효율적인 게임서버에 대한 연구는 매우 부족한 실정이다. 본 논문은 가상화 기반으로 SNG게임서버를 설계 및 구현한다. 또한 가상화 기반 분산 게임서버의 CPU 사용률과 Memory 사용량을 분석하여 게임서버의 자원 활용률을 보인다. 이를 토대로 SNG게임서버 환경구축의 기반지식을 제공한다.