• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.251-258
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• 2011

The existing evaluation systems based on financial performance summarize the information about past results and focus on short-term performance, and so they have the limits to explain the future value of firms and to make a long-term strategic performance. By this reason, as a way to increase the future value, the development of the integrated performance evaluation system with which we may manages financial performance and knowledge assets together has been required recently. This study puts together various researches for the evaluation of knowledge assets, and analyzes the existing studies for the domestic medical devices industry and the tendency of introduction for business practice. Under this analysis, this study develops the knowledge asset evaluation indexes for medical devices industry by using the Balanced Score Card (BSC) of Kaplan & Norton(1992), and then presents the evaluation model by applying the Analytic Hierarchy Process (AHP) of Saaty(1980) to get the weight for each index. With the final evaluation model, we can calculate the evaluation score combined with both the quantitative indexes and the qualitative indexes at once.

• Knowledge Management Research
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• v.10 no.2
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• pp.85-103
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• 2009

Web 2.0, characterized as openness, sharing, and participation, has enabled Internet users to easily generate a variety of contents, and to share them through Web 2.0 services. Knowledge search service (KSS) is positioning itself as one of typical Web 2.0 services. Yet, few studies have sharpened our understanding of users' knowledge sharing behavior in the KSS environment. In order to address this knowledge void, this paper attempts to explore antecedents of their usage behavior in the KSS environment. Typically, they utilize stored knowledge and share their knowledge simultaneously. Considering this characteristic, our study regards service usage intention and knowledge sharing intention as final dependent variables. This study advances a research model based on Bhattacherjee's expectation-confirmation model, which is expanded by incorporating trust belief. Because of the openness of KSS, trust belief is believed to play a critical role in forming users' service usage intention and knowledge sharing intention. Furthermore, this study examines the difference of the antecedents' effects in terms of users' gender. We collected data from 275 respondents who have experience in using KSS. PLS (partial least squares) was employed for the analysis of the data. Analysis results confirm the important role of user satisfaction and trust belief in the formation of users' service usage intention and knowledge sharing intention. More importantly, trust belief has a more salient effect on knowledge service usage intention than user satisfaction. This study also shows the moderating role of users' gender. Finally, this paper provides managerial guidance on strategic planning aimed at improving users' service usage intention and knowledge sharing intention in the KSS environment.

• Journal of the Korean Society for information Management
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• v.20 no.4 s.50
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• pp.277-301
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• 2003

Knowledge Management is presented as the management method having the survival and competition of enterprise under variously changing management environment. Knowledge Management is introduced recently as successful survival strategy of advanced enterprise. Scientifically, however, the definition. study model and propulsion method of KM leave much to be desired, and now it has become the subjects of active study among scholars. To creation of the competitive power of the company have to be important knowledge based continuous innovation. That is to say, the knowledge management means a lot to knowledge assets included knowledge, knowledge creating, sharing, and acting This study aims to propose models on the research result based a case study of the financial industry in knowledge creating processes(SECI) and deriving knowledge management styles in the flied works of the bank.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.421-428
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• 2006

Intelligent Tutoring System(ITS), which offers individualized learning environment that consider many learners' variable, is realized by the effective alternative to take the place of domain expert. Accordingly, research on Learning Companion System(LC) is currently noticing. However, to develop LCS which applies effective interaction, it is necessary to combine several LCs, and personalized knowledge base have to be made first. Therefore, in this paper, we propose the 'Knowledge Base Object Medel', which is based on connectionist' in cognition structure, represents learner's knowledge to self-learnig object, and grows adaptive object by proprietor, verify the validity. This model lays the groundwork for design of personalized knowledge base, offers clue to development of adaptive ITS using knowledge base object.

• Journal of the Korean Society for information Management
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• v.19 no.4
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• pp.349-381
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• 2002

The 21st century survive only who creating, taking, and managing to knowledge. Digital contents industry becomes to the core in the future. That is, to win in a competition have to the digitalizing knowledge contents to all knowledge and information resources. Therefore, it needs to the digital contents management and the distribution framework. This study aims to propose a model stages in the knowledge contents-decision process, KM Matrix, and KMI Score founded on digital contents framework and diffusion of innovation.

• Journal of The Korean Association of Information Education
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• v.16 no.1
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• pp.71-80
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• 2012

This study aimed to investigate technological pedagogical and content knowledge(TPACK) model, and to apply this model to preservice education. To perform this study, TPACK survey instrument was distributed to 142 preservice teachers who took technology integration course. The result showed that technology and content knowledge improved significantly, and pedagogical and pedagogical content knowledge did not show meaningful differences among 7 sub-categories. Based on the result of this study, we discussed the improvement of technological and content knowledge, and pedagogical knowledge. Also, we suggested that (preservice) teacher education should consider the combination of technological, pedagogical, and content knowledge in Korea.

• Journal of the Ergonomics Society of Korea
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• v.29 no.4
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• pp.631-637
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• 2010

The aim of affective engineering is to develop a new product by translating customer affections into design factors. Affective data have so far been analyzed using a multivariate statistical analysis, but the affective data do not always have linear features assumed under normal distribution. Rough sets model is an effective method for knowledge discovery under uncertainty, imprecision and fuzziness. Rough sets model is to deal with any type of data regardless of their linearity characteristics. Therefore, this study utilizes rough sets model to extract affective knowledge from affective data. Four types of scent alternatives and four types of sounds were designed and the experiment was performed to look into affective differences in subject's preference on air conditioner. Finally, the purpose of this study also is to extract knowledge from affective data using rough sets model and to figure out the relationships between rough sets based affective engineering method and statistical one. The result of a case study shows that the proposed approach can effectively extract affective knowledge from affective data and is able to discover the relationships between customer affections and design factors. This study also shows similar results between rough sets model and statistical method, but it can be made more valuable by comparing fuzzy theory, neural network and multivariate statistical methods.

• Knowledge Management Research
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• v.22 no.3
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• pp.91-106
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• 2021

With the recent rapid development of deep learning technology, the demand for analyzing huge text documents in the national R&D field from various perspectives is rapidly increasing. In particular, interest in the application of a BERT(Bidirectional Encoder Representations from Transformers) language model that has pre-trained a large corpus is growing. However, the terminology used frequently in highly specialized fields such as national R&D are often not sufficiently learned in basic BERT. This is pointed out as a limitation of understanding documents in specialized fields through BERT. Therefore, this study proposes a method to build an R&D KoBERT language model that transfers national R&D field knowledge to basic BERT using further pre-training. In addition, in order to evaluate the performance of the proposed model, we performed classification analysis on about 116,000 R&D reports in the health care and information and communication fields. Experimental results showed that our proposed model showed higher performance in terms of accuracy compared to the pure KoBERT model.

• Genomics & Informatics
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• v.6 no.4
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• pp.202-209
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• 2008

Biological pathways are known as collections of knowledge of certain biological processes. Although knowledge about a pathway is quite significant to further analysis, it covers only tiny portion of genes that exists. In this paper, we suggest a model to extend each individual pathway using a microarray expression data based on the known knowledge about the pathway. We take the Rosetta compendium dataset to extend pathways of Saccharomyces cerevisiae obtained from KEGG (Kyoto Encyclopedia of genes and genomes) database. Before applying our model, we verify the underlying assumption that microarray data reflect the interactive knowledge from pathway, and we evaluate our scoring system by introducing performance function. In the last step, we validate proposed candidates with the help of another type of biological information. We introduced a pathway extending model using its intrinsic structure and microarray expression data. The model provides the suitable candidate genes for each single biological pathway to extend it.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.290-294
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• 2009

When we are visiting unfamiliar huge public places, it is hard to know what, how, and where to go. For solving these problems, we have suggest a user guide system, and a knowledge model which is built to support the system. High intelligence guidance system needs to react the user's context more spontaneously, which could be obtained when a system aware both the location and process coordinately. In this paper, we will show how our knowledge model is designed to enable the system to interpret simultaneously both of them.