• Management & Information Systems Review
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• v.2
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• pp.169-193
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• 1998

Case- based reasoning(CBR) offers a new approach for developing knowledge based systems. Unlike the rule-based paradigm, in which domain knowledge is encoded in the form of production rules, in the case-based approach the problem solving experience of the domain expert is encoded in the form of cases stored in a casebase(CB). CBR allows a reasoner (1) to propose solutions in domains that are not completely understood by the reasoner, (2) to evaluate solutions when no algorithmic method is available for evaluation, and (3) to interprete open-ended and ill-defined concepts. CBR also helps reasoner (4) take actions to avoid repeating past mistakes, and (5) focus its reasoning on important parts of a problem. Owing to the above advantages, CBR has successfully been applied to many kinds of problems such as design, planning, diagnosis and instruction. In this paper, I propose case-based DSS(CBDSS). CBDSS is an intelligent DSS using CBR technique. CBDSS consists of interface, case-based reasoner, maintainer, casebase management system, domain dependent CB, domain independent CB, and so on.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.165-165
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• 2023

Streamflow prediction is a critical task in water resources management and essential for planning and decision-making purposes. However, the streamflow prediction is challenging due to the complexity and non-linear nature of hydrological processes. The transfer learning is a powerful technique that enables a model to transfer knowledge from a source domain to a target domain, improving model performance with limited data in the target domain. In this study, we apply the transfer learning using the Informer model, which is a state-of-the-art deep learning model for streamflow prediction. The model was trained on a large-scale hydrological dataset in the source basin and then fine-tuned using a smaller dataset available in the target basin to predict the streamflow in the target basin. The results demonstrate that transfer learning using the Informer model significantly outperforms the traditional machine learning models and even other deep learning models for streamflow prediction, especially when the target domain has limited data. Moreover, the results indicate the effectiveness of streamflow prediction when knowledge transfer is used to improve the generalizability of hydrologic models in data-sparse regions.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.511-515
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• 2001

Many intelligent agent systems are known to incorporate BDI architecture for cognitive reasoning. Since this architecture contains all the knowledge of world model and reasoning rule, it is very complex and difficult to handle. This paper describes a methodology to design and implement BDI architecture, BDIAXml based on XML for multi-agent systems. This XML-based BDI architecture is smaller than any other BDI architecture because it separates knowledge for reasoning from domain knowledge and enables knowledge sharing using XML technology. Knowledge for BDI mental state and reasoning is composed of specific XML files and these XML files are stored into a specific knowledge server. Most systems using BDIAxml architecture can access knowledge from this server. We apply this BDIAXml system to domain of Hospital Information System and show that this architecture performs more efficiently than other BDI architecture system in terms of knowledge sharing, system size, and ease of use.

• Korean Journal of Cognitive Science
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• v.16 no.4
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• pp.271-285
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• 2005

An experiment was conducted to investigate the effect of three types of prior knowledge (domain related knowledge, summary-writing strategy knowledge, and neutral unrelated knowledge) and two types (analytic and wholistic) of cognitive styles on the quality of the summary writing of a descriptive text. The results showed that learning domain-related knowledge and summary-writing-strategy knowledge increased the level of understanding of the target text and the quality of the summary; the former operating mainly at the understanding phase, and the latter operating mainly during the summary planning and producing phases. The effect of the types of cognitive style was found somewhat limited but mainly operating In the process of planing the summary. Other features of time course in writing a summary were further discussed.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.311-320
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• 2006

Knowledge management strategy has become a one of the most important factors creating and maintaining the business opportunities. In this paper, I present a KM-ePAY typology to investigate the role of knowledge sharing strategy in the electronic payment domain. Specifically, I examine the characteristics of four types of electronic payment systems based on the confidence and efficiency that characterize the feature of electronic payment media and identify appropriate knowledge sharing approaches for each component. In conclusion, my findings indicate that knowledge sharing approaches which are align with the characteristics of electronic payment give a way both to increase relationship commitment and to optimize process over electronic payment transactions.

• Journal of Engineering Education Research
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• v.24 no.3
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• pp.50-57
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• 2021

Although the mathematics education process in AI education is a very important issue, little cases are reported in developing effective methods on AI and mathematics education at the university level. The universities cover all fields of mathematics in their curriculums, but they lack in connecting and applying the math knowledge to AI in an efficient manner. Students are hardly interested in taking many math courses and it gets worse for the students in humanities, social sciences and arts. But university education is very slow in adapting to rapidly changing new technologies in the real world. AI is a technology that is changing the paradigm of the century, so every one should be familiar with this technology but it requires fundamental math knowledge. It is not fair for the students to study all math subjects and ride on the AI train. We recognize that three key elements, SW knowledge, mathematical knowledge, and domain knowledge, are required in applying AI technology to the real world problems. This study proposes a modular approach of studying mathematics knowledge while connecting the math to different domain problems using AI techniques. We also show a modular curriculum that is developed for using math for AI-driven autonomous driving.

• Child Health Nursing Research
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• v.10 no.2
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• pp.165-172
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• 2004

The main purpose of this study is to examine the concepts appeared on research and provide future research directions in field of child health nursing. 205 studies of the total 318 studies had been analyzed first for the concepts of the client domain and this time 113 studies were analyzed for the practice, the client-nurse and the environmental domain in nursing. The practice domain includes mentalistitic, enactment, knowledge utilization, role related phenomenon, the client-nurse domain includes touch, communication, interaction phenomenon, and the environmental domain includes physical, social, symbolic environment. All were originally published between 1990 and 2000 in Korea. An analysis of concepts for this study was used the metaparadigm framework for nursing proposed by H. S. Kim(2000). 1. 103 studies belonged to the practice domain. Among them, 56(54％) studies used concepts related to enactment phenomenon like education(21.4％), giving information(7.1％), breast feeding(5.4％), caring(5.4％), airway suction(5.4％), nonnutritive sucking(5.4％). 44(43％) studies used concepts related to knowledge utilization like program development and evaluation of smoking, mother-infant interaction, home health nursing, obesity management. And only 3(3％) studies used role related concepts like quality of nursing, direction of health education, contents of child health nursing education. 2. Only 2(0.006％) studies belonged to the client-nurse domain. One concept is empathy in communication phenomenon and the other concept is role conflict in interaction phenomenon. 3. 8(0.02％) studies belonged to the environmental domain. Among them, 3 studies related to physical environment like space, noise and 5 studies related to social environment like social support, home environment. But the concept of symbolic environment was not used. The findings of this study provide the evidence that research related to the client-nurse domain and the environmental domain should be conducted actively to improve the practice of child health nursing. So that the research in field of child health nursing should be dealt with the concepts of four domains to develop knowledge systematically.

• Knowledge Management Research
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• v.10 no.2
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• pp.49-63
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• 2009

In this study, sub domain of flow was investigated on literature survey, and suggested of the measuring method of web-site flow and its simulation analysis. Constructing of measuring method of flow, and using this method what-if analysis was simulated when several condition changed. Using causal map approach to extract knowledge from web-site domain experts and to derives a causal relationship of knowledge. Specially, in our study, describes method of developing and building causal map, and suggests guide line of this method on practical application. This research results show that web-site flow starts "direct searching" or "interesting of special issue(domain)", and when challenges of web-site were accorded with user's skills web-site flow grows. Further, in the web-site, information searching intention results in increase of user's duration time and experience flow to discovery new interesting issues in this process. If user's web-site of interaction is increased, awareness of environment conditions decreased, finally, user's telepresense results in increased web-site flow. This paper contained thai this method make used of measuring flow in the web-site and developing of practical strategy.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.525-534
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• 2006

Ontology specifies the knowledge in a specific domain and defines the concepts of knowledge and the relationships between concepts. It is possible to provide the service based on the semantic web through the ontology. Therefore, to specify and define the knowledge in a specific domain, it is required to generate the ontology which conceptualizes the knowledge. Accordingly, to search the information of potential customers for home-delivery marketing of post office, we design the specific domain to generate the ontology based on the semantic web in this paper. And we propose how to retrieve the information, using the generated ontology. We implement the data search robot which collects the information based on the generated ontology. Also, we confirm that the ontology and the search robot perform the information retrieval exactly.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.291-296
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• 2007

The ontology has been used widely in recent years with its aim to accumulate knowledge that machine can comprehend. We believe that machine can manage and analyze information on its own using the ontology. In this paper, we propose an algorithm that allows us to extract properties of ontology instances from structured information already existing in web documents. In particular, by stratification of the domain knowledge that is composed of property information, we were able to make the algorithm better and improve the quality of extraction results. In our experiments with 20 thousands targeted documents, we were able to extract property information with 83% confidence.