• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.409-413
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• 2005

The logical analysis of data(LAD) is an effective Boolean-logic based data mining tool. A critical step in analyzing data by LAD is the pattern generation stage where useful knowledge and hidden structural information in data is discovered in the form of patterns. A conventional method for pattern generation in LAD is based on term enumeration that renders the generation of higher degree patterns practically impossible. In this paper, we present a new optimization-based pattern generation methodology and propose two mathematical programming medels, a mixed 0-1 integer and linear programming(MILP) formulation and a well-studied set covering problem(SCP) formulation for the generation of optimal and heuristic patterns, respectively. With benchmark datasets, we demonstrate the effectiveness of our models by automatically generating with much ease patterns of high complexity that cannot be generated with the conventional approach.

• The Transactions of the Korea Information Processing Society
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• v.5 no.3
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• pp.662-670
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• 1998

In order to overcome the problems with first generation expert systems at the symbol level, recently various knowledge level development techniques of second generation expert systems have been proposed. But, these techniques are conceptual modelling techniques. This paper modifies and complements these conceptual modelling techniques and proposes a Task Object Modelling (TOM) technique as a practical knowledge level expert system development technique. This paper defines a Task Object(TO) as a knowledge unit consisted of a goal, execution conditions, behaviour knowledge, and so on. And, we define a Task Object Diagram(TOD) to depict structual, dynamic, and functional aspects of TO easily. We also define Inference Types as basic units to describe behaviour knowledge of TOs. In order to utilize the proposed TOM technique as not a simple conceptual modelling technique but a practical second generalion expert system development technique, we implement a TOD editor, a TO editor, and TO processing algorithm based on the state of TOs. Also we implement a Inference Types Library, in which each inference type is corresponded to an IRE(Jntelligent Rules Element) method, to transform the defined inference types into IRE methods automatically.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.2
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• pp.102-110
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• 2017

Current word sense disambiguation techniques employ various machine learning-based methods. Various approaches have been proposed to address this problem, including the knowledge base approach. This approach defines the sense of an ambiguous word in accordance with knowledge base information with no training corpus. In unsupervised learning techniques that use a knowledge base approach, graph-based and similarity-based methods have been the main research areas. The graph-based method has the advantage of constructing a semantic graph that delineates all paths between different senses that an ambiguous word may have. However, unnecessary semantic paths may be introduced, thereby increasing the risk of errors. To solve this problem and construct a fine-grained graph, in this paper, we propose a model that iteratively constructs the graph while eliminating unnecessary nodes and edges, i.e., senses and semantic paths. The hybrid similarity estimation model was applied to estimate a more accurate sense in the constructed semantic graph. Because the proposed model uses BabelNet, a multilingual lexical knowledge base, the model is not limited to a specific language.

• Journal of The Korean Association For Science Education
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• v.24 no.6
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• pp.1106-1117
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• 2004

The purposes of this study were to analyze types of scientific emotion word and to investigate the relationship between the ISE(Index of Scientific Emotion) and the ability of science-knowledge generation in subjects' scientific observation and rule-discovery. The subjects were asked to perform four scientific tasks. The tasks were developed that are suitable for scientific observation and rule-discovery. In performing tasks, the subjects were asked to describe their generated science-knowledge and scientific emotion through self-report questionnaire, performing each task. The strength of their scientific emotion was also measured using adjective emoticon check lists. In subjects' scientific observing, they showed 33.3% of interest emotion which was the biggest, 15.0% of acceptance emotion, and 11.3% of love emotion, respectively. In scientific rule-discovering, types of emotion were shown as 23.8% of interest, 21.5% of disgust, and 10.8% of acceptance, respectively. In addition, ability of science-knowledge generation was significantly correlated to ISE.

• Journal of Korean Academy of Nursing
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• v.48 no.6
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• pp.637-655
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• 2018

Purpose: The purpose of this qualitative study is to investigate the nature of tacit nursing knowledge practiced in the clinical field in Korea using hybrid models, and to clarify the definitions and attributes of the concept. Methods: The definition and nature of tacit nursing knowledge, obtained through a review of the extensive literature at the theoretical stage of the research, and the analysis of the in-depth interview data conducted by the career nurses in the fieldwork stage, are compared and analyzed. Results: The tacit nursing knowledge was found in three dimensions as knowledge related to the person, the clinical situation work context, the self, the others, and the task. The tacit nursing knowledge was defined as personal nursing knowledge and artistic skills that show up as unconscious behavior patterns, learned informally, and internalizedthrough repeated clinical practice experience based on professional nursing knowledge. Conclusion: Tacit nursing knowledge has been widely used in clinical practice and has been shown to have a great impact, directly or indirectly, on clinical nursing. Therefore, individual and organizational efforts are needed for validation and clarification using the generation, sharing, collection, and peer review of sound implicit nursing knowledge to ensure that it is properly applied.

• Knowledge Management Research
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• v.18 no.3
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• pp.81-99
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• 2017

This study is to compare the main subjects of domestic and foreign knowledge management research in terms of keywords and to clarify whether domestic knowledge management research reflects research trends in overseas knowledge management research. Specifically, we try to find out whether the central activities such as knowledge sharing, knowledge generation, and acquisition, which are knowledge management activities of knowledge management research, are being studied without bias. In order to analyze this, we analyzed the data of domestic and foreign knowledge management research for the last 5 years from 2012 to 2016. In Korea, the Knowledge Management Society of Korea collected 167 papers and 787 keywords, and collected 132 papers and 640 keywords from the Korea Society of Management Information Systems in order to distinguish the research areas. Overseas papers collected 315 papers and 1,746 keywords published by Emerald. Also, we collected 382 papers and 1,633 keywords in the Korean Management Review and collected 646 papers and 2,879 keywords in the Korean Business Education Review. Frequency analysis and network analysis of 1,642 papers and 7,685 keywords are summarized as follows. The Knowledge Management Society of Korea has focused on knowledge sharing, and in 2016, interest in knowledge transfer and knowledge search has shifted. The Journal of Knowledge Management, which is published by Emerald, has been a major concern for knowledge transfer and knowledge sharing. The research trends of the Korea Society of Management Information Systems to distinguish a clear identity of knowledge management research are focusing on smart area and mobile domain such as information security domain, cloud, smart phone, and smart work. In the Korea Society of Management Information Systems research, the main subject of knowledge sharing is also commonly found.

• Knowledge Management Research
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• v.2 no.1
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• pp.83-94
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• 2001

It is a challenging task to introduce and apply a theoretical concept like KM (Knowledge Management) to the corporate management by formulating such notion into a computer-based system. Apart from that, a company who suffers financially will be very much reluctant to employ KM, a solution that will not make an immediate impact on profit generation. Nonetheless, the perception of life-long workplace is being replaced by that of life-long career in today's society, and consequently it has become a key importance for the management to minimizing the Joss of valuable knowledge that results from frequent shift of manpower. Furthermore, knowledge is now regarded as a key to corporate competitiveness as its value has become a more important factor than that of physical resource in estimating a company's value. It is therefore necessary to transform such implicit knowledge that one possesses in his/her mind to a formation so that a company can achieve the ultimate goal of implementing KM: increase of profit and cost reduction. The objective of this research is to look into the case examples of the way in which Samsung Electronics implemented KM and help set the direction for those companies who consider employing KM into their corporate system.

• Journal of The Korean Association For Science Education
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• v.23 no.4
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• pp.430-441
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• 2003

The purpose of this study was to investigate the effects of students' prior knowledge on scientific reasoning in solving a pendulum task with a computer simulation. Subjects were 60 Korean students: 27 fifth-grade students from an elementary school and 33 seventh grade students from a middle school located in a city with 300,000 people. This study adapted a pendulum task presented with a computer simulation on which subjects would use a pattern of multivariable causal inferences. The subjects were interviewed individually in a three-phase structured interview by the researcher and three assistants while he/she was investigating the pendulum task. This study showed that most students across grades focused heavily on demonstrating the primacy of their prior knowledge or their current hypothesis. In addition, students' theories that are part of one's prior knowledge have a significant impact on formulating, testing, and revising hypotheses. Therefore, this study supported the notion that students' prior knowledge had a strong effect on students' experimental intent and hypothesis evaluation.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.99-106
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• 1998

In this paper, we have constructed an expert system for semiconductor chip encapsulation which combines a knowledge-based system with CAE software. The knowledge-base module includes heuristic and pre analysis knowledge for evaluation and redesign. Evaluation of the initial design and generation of redesign recommendations can be developed from the rules as applied to a given chip package. The CAE programs can be used for simulating the filling and packing stage of encapsulation process. The expert system is a new tool which enables package design or process conditions with high yields and high productivity.

• The Journal of Society for e-Business Studies
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• v.7 no.1
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• pp.75-86
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• 2002

In this study, we proposed design issues and structure of a web mining system and develop a system for the purpose of knowledge integration under world wide web environments resulted from our developing experiences. The developed system consists of three main functions： 1) gathering documents utilizing a search agent; 2) determining similarity coefficients between any two documents from term frequencies; 3) clustering documents based on similarity coefficients. It is believed that the developed system can be utilized for discovery of knowledge in relatively narrow domains such as news classification, index term generation in knowledge management.