• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.3
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• pp.91-107
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• 2000

The linear programming model is a special form of useful knowledge that is embedded in a database. Since formulating models from scratch requires knowledge-intensive efforts, knowledge-based formulation support systems have been proposed in the Decision Support Systems area. However, they rely on the assumption that sufficient domain knowledge should already be captured as a specific knowledge representation form. Hence, the purpose of this paper is to propose a methodology that finds useful knowledge on building linear programming models from a database. The methodology consists of two parts. The first part is to find s first-cut model based on a data dictionary. To do so, we applied the General Problem Solver(GPS) algorithm. The second part is to discover a second-cut model by applying neural network technique. An illustrative example is described to show the feasibility of the proposed methodology.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.613-614
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• 2006

Design data, information, and knowledge have complex associations with each other. Systems related with the management of the data, information, and knowledge are various, and the representations are numerous. Therefore it is difficult to construct a knowledge based design system with a full association knowledge for supporting the design tasks. In this research, OWL based ontology model for an excavator design is developed for the representation of the relationships. Also an ontology model is used to develop the knowledge based excavator design system.

• Journal of The Korean Association For Science Education
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• v.33 no.7
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• pp.1385-1402
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• 2013

This study analyzes pre-service teachers' PCK dealing with visualization of the contents related to boiling point elevation and teaching methods in mock-lessons. As a result of analyzing pre-service teachers' knowledge based on PCK factors, most of the pre-service teachers accentuated on understanding boiling point elevation conceptually, whereas some of the others inclined to make students understand boiling point elevation in a scientific way, let the kids use numerical formulas to describe the concept, and motivate them to learn through the examples in real life. The pre-service teachers represented majority of the important facts of boiling point elevation as the knowledge required to understand things conceptually. However, they did not focus on improving the scientific thinking and inquiring levels of the students. Also, the pre-service teachers tended to teach at the level and order of the textbook. In some other cases, they considered the vocabularies and materials in the textbook (which could have been highlighted in the editing sequence) as the main topic to learn, or regarded the goal as giving students the ability to solve exercises in the textbook. It turned out that the pre-service teachers had a low level of knowledge of their students. It is recommended that they should make use of the materials given (such as data related to the misconception of students) during the training session. The knowledge of teaching and evaluating students was described superficially by the pre-service teachers; they merely mentioned the applications of models, such as the cyclic model and discovery learning, rather than thinking of a method related to the goals, or listed general assessment methods.

• Asia pacific journal of information systems
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• v.8 no.1
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• pp.43-64
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• 1998

Cooperative query answering is a research effort to develop a fault-tolerant and intelligent database system using the semantic knowledge base constructed from the underlying database. Such knowledge base has two aspects of usage. One is supporting the cooperative query answering process for providing both an exact answer and neighborhood information relevant to a query. The other is supporting ongoing maintenance of the knowledge base for accommodating the changes in the knowledge content and database usage purpose. Existing studies have mostly focused on the cooperative query answering process but paid little attention to the dynamic knowledge base maintenance. This paper proposes a multi-level knowledge representation framework called Knowledge Abstraction Hierarchy(KAH) that can not only support cooperative query answering but also permit dynamic knowledge maintenance, On the basis of the KAH, a knowledge abstraction database is constructed on the relational data model and accommodates diverse knowledge maintenance needs and flexibly facilitates cooperative query answering. In terms of the knowledge maintenance, database operations are discussed for the cases where either the internal contents for a given KAH change or the structures of the KAH itself change. In terms of cooperative query answering, four types of vague queries are discussed, including approximate selection, approximate join, conceptual selection, and conceptual join. A prototype system has been implemented at KAIST and is being tested with a personnel database system to demonstrate the usefulness and practicality of the knowledge abstraction database in ordinary database application systems.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.783-790
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• 2002

This paper proposes a fuzzy Pr/T net representation of interval-valued fuzzy set reasoning, where fuzzy production rules are used for knowledge representation, and the belief of fuzzy production rules are represented by interval-valued fuzzy sets. The presented interval-valued fuzzy reasoning algorithm is much closer to human intuition and reasoning than other methods because this algorithm uses the proper belief evaluation functions according to fuzzy concepts in fuzzy production rules.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.3
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• pp.427-440
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• 1996

Constraint networks are a major approach to knowledge representation in Concurrent Engineering (CE) systems. The networks model various factors in CE as constraints linked by shared variables. Many systems have been developed to assist constraint network processing. While these systems can be useful, their underlying assumption that a solution must simultaneously satisfy all the constraints is often unrealistic and hard to achieve. Proposed in this paper is a hierarchical representation of constraint networks using priorities, namely Prioritized Constraint Network (PCN). A mechanism to propagate priorities is developed, and a new satisfiability definition taking into account the priorities is described. Strength of constraint supporters can be derived from the propagated priorities. Several properties useful for investigating PCN's and finding effective solving strategies ore developed.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.1-30
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• 2013

The capitalization of know-how, knowledge management, and the control of the constantly growing information mass has become the new strategic challenge for organizations that aim to capture the entire wealth of knowledge (tacit and explicit). Thus, knowledge mapping is a means of (cognitive) navigation to access the resources of the strategic heritage knowledge of an organization. In this paper, we present a new mapping approach based on the Boolean modeling of critical domain knowledge and on the use of different data sources via the data mining technique in order to improve the process of acquiring knowledge explicitly. To evaluate our approach, we have initiated a process of mapping that is guided by machine learning that is artificially operated in the following two stages: data mining and automatic mapping. Data mining is be initially run from an induction of Boolean case studies (explicit). The mapping rules are then used to automatically improve the Boolean model of the mapping of critical knowledge.

• Journal of Korean Library and Information Science Society
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• v.16
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• pp.129-157
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• 1989

Through this study, some considerations to be taken into account in order to construct the user model for the user friendly system which can provide each individuals user armed with varied intellectual level with the relevant information, can be summarized as follows : (1) The user' ability to use the system and users' subject knowledge, the distribution of the users' level knowledge should be considered for the decision of the typed of interaction between the users and the system. (2) the knowledge of the user models should include the following kinds of knowledge inharmony with one another, 1. Standard user knowledge which represents a general characteristic of user group, 2. individual user knowledge which represents an individual's unique characteristic, 3. Long-term user knowledge which represents the education level and subject background of users, 4. short-term user knowledge which represents the purpose of information science and information need by users (3) As knowledge generation technique, both the implicit method and explicit method should be a n.0, pplied, observation of the system during the interaction, and explicit method generates the knowledge by the user's answering the questions already made by the system. (4) The frame technique as the knowledge representation for the user-modelling in which user-knowledge is represented in a limited situation and in a qualitative aspects, can be recommended. The frame is adequated for the explanation of structured situation, and for the processing the present situation by inferring the previous experiences.

• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.21-31
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• 2012

The virtual reality consists of a virtual space constructed similar to the reality and agents residing in it. Our virtual space refers to an orderly space that is governed by such physical properties as mass, gravity, friction, and associated rules on top of the usual visual rendering. To construct this virtual world we are to develop virtual agents behaving like humans and the environment surrounding them. In order to improve the existing reactive agents designed to act to their designers' dictation in predetermined space or memory into autonomous agents, we need diverse kinds of knowledge among others related to the spaces for the agents to act in. Our design and implementation focuses on the spatial knowledge among those diverse aspects of knowledge required. The developed knowledge representation scheme is used on a basis for realistic and efficient physical cyber-environment, and as the knowledge structure to simulate the virtual agents' knowledges on spaces.

• Korean Journal of Child Studies
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• v.34 no.6
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• pp.139-158
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• 2013

Karmiloff-Smith was first to propose the 'Representational Redescription model'. It describes a process through which children elaborate their knowledge from the unconscious and implicit levels to the conscious and explicit levels. The model also assumes that children in perfectly explicit levels are able to express their own representation of knowledge verbally. This study was conducted to investigate Karmiloff-Smith's Representational Redescription(RR) model(1990, 1992, 1999) within the drawing domain. Additionally, how verbalization training influences children's development of representational redescription in drawing were also examined. First, 331 children (4- to 6-year-olds and an older comparison group of 7- to 9-year-olds) were asked to create six drawings of both familiar and novel topics. From these drawings, children were measured for procedural rigidity and developmental differences. Thereafter 80 5-year-olds children who were not able to manipulate their drawings with flexibility were selected. They were divided into an experimental group and two control groups. A group of verbalization training was given a session using 5 tasks. Compared to the control groups, children who practiced verbalization in the training group showed more advanced levels of representation than their previous levels in the pretest. The results were interpreted as meaning that verbalization is likely to facilitate children's reorganization of implicit knowledge within the drawing domain and to transfer this toward explicit forms. Further research needs to pay more attention to the educational applications of learning processes based on representational redescription.