• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.282-296
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• 2010

OWL is an ontology language for the Semantic Web, and suited to modelling the knowledge of a specific domain in the real-world. Ontology also can infer new implicit knowledge from the explicit knowledge. However, the modeled knowledge cannot be complete as the whole of the common-sense of the human cannot be represented totally. Ontology do not concern handling nonmonotonic reasoning to detect incomplete modeling such as the integrity constraints and exceptions. A default rule can handle the exception about a specific class in ontology. Integrity constraint can be clear that restrictions on class define which and how many relationships the instances of that class must hold. In this paper, we propose a practical reasoning system for open and closed-world reasoning that supports a novel hybrid integration of ontology based on open world assumption (OWA) and non-monotonic rule based on closed-world assumption (CWA). The system utilizes a method to solve the problem which occurs when dealing with the incomplete knowledge under the OWA. The method uses the answer set programming (ASP) to find a solution. ASP is a logic-program, which can be seen as the computational embodiment of non-monotonic reasoning, and enables a query based on CWA to knowledge base (KB) of description logic. Our system not only finds practical cases from examples by the Protege, which require non-monotonic reasoning, but also estimates novel reasoning results for the cases based on KB which realizes a transparent integration of rules and ontologies supported by some well-known projects.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.133-141
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• 2012

Virtual project organization may be recognized as one of the promising business models in which many knowledge sources externalize through cross boundaries of knowledge-based organizations. This paper proposes a knowledge competence evaluation of virtual project organization based on the following perspectives: 1) Individual knowledge perspective, 2) Activity-oriented knowledge perspective, and 3) Knowledge-driven social network perspective. In the framework, individual knowledge competence having experienced or learned from knowledge-based activities and virtual networks in the project, should be evaluated according to the assumption that knowledge and collaboration competence depends on the activities and networks acquired proportionally by the past participation to projects. An illustrative SI example is given in order to validate the proposed evaluation and computing procedure.

• Korean Journal of Child Studies
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• v.21 no.3
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• pp.41-51
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• 2000

This study discusses the interpretation and application of a post modern perspective to child development knowledge and early childhood teacher education. The survey of literature focused on the post modern approach to child development knowledge and early childhood teacher education, research in the reassessment of child development knowledge as it is challenged by the post modern perspective, and deconstruction of both child development knowledge and early childhood teacher education. It was concluded that child development knowledge is necessary but insufficient to early childhood teacher education. In the post modern perspective, the movement toward fostering "reflective practitioners" and basic knowledge base is more significant. Therefore, the responsibility of academics is to walk the fine line between presenting a formal knowledge base so that students gain assumption to guide their thinking and practice, critiquing both theory and derived practices.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.290-293
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• 2000

Knowledge discovery refers to the overall process of discovering useful knowledge from data. 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 DSS area. However, they rely on the strict 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 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.

• Knowledge Management Research
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• v.7 no.1
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• pp.65-80
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• 2006

Recently, Korean economy is boosted by the active introduction of many venture businesses full of entrepreneurship. It has been widely accepted implicitly that success of the venture business originates from unique style of knowledge management. This assumption looks natural when we consider the fact that success of the venture business heavily depends on differentiated intelligent asset or knowledge. However, such implicit belief has never been tested empirically. To fill the research void like this, this paper proposes an empirical derivation of key success factors from the venture businesses listed in KOSDAQ. To add rigor to our results, we performed regression analysis by using the derived key success factors as independent variables, and introducing organization efficiency, job satisfaction, and accomplishment motivation as dependent variables. Regression results showed that our approach is justified from the statistical perspective.

• 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.

• Journal of Information Processing Systems
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• v.7 no.3
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• pp.549-560
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• 2011

Vote validity proof and verification is an efficiency bottleneck and privacy drawback in homomorphic e-voting. The existing vote validity proof technique is inefficient and only achieves honest-verifier zero knowledge. In this paper, an efficient proof and verification technique is proposed to guarantee vote validity in homomorphic e-voting. The new proof technique is mainly based on hash function operations that only need a very small number of costly public key cryptographic operations. It can handle untrusted verifiers and achieve stronger zero knowledge privacy. As a result, the efficiency and privacy of homomorphic e-voting applications will be significantly improved.

• Journal of the Korean Society for information Management
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• v.3 no.1
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• pp.70-102
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• 1986

This study is an attempt to develop a knowledge base with Inference mechanism for document retrieval, which is the core element of expert system. The purpose of this study is to design the knowledge base in order to intellectually process user queries eventually improving the effectiveness of information retrieval, under the assumption that the user who wants to search a certain subject generally lack the prior knowledge about that subject. In this paper, some characteristics of Korean complex nouns are structurally analyzed and are represented in the knowledge base.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.454-458
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• 2015

A number of practices for sharing knowledge has been recommended in the literature. These practices, however, are considered to be applicable, universally. This assumption is challenged by this paper which empirically explores the relationship between national culture and knowledge sharing practices in the context of procuring educational buildings in Saudi Arabia. The paper reports on a research study with the aim to identify whether national culture dimensions could be significant variables that impact upon staff preferences in relation to project knowledge sharing practices. The paper critically reviews the literature to identify appropriate measures for knowledge sharing practices. It explores the means by which public sectors professional exchange project knowledge; evaluates policies and level of technical support needed to facilitate knowledge sharing, then proceeds to how employees perceive the benefits they will gain by practicing project knowledge sharing, and their role in this process. The paper tests the relationships among the research constructs based on data collected from 115 project managers responsible for the procurement of educational buildings in Saudi Arabia. The paper provides empirical evidence that the national culture has a significant influence on staff preferences. In light of the research findings the paper concludes with practical recommendations for project knowledge sharing practices that are in line with staff preferences and their cultural orientation. The recommendations should facilitate a more effective application of knowledge sharing practices.

• IE interfaces
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• v.3 no.2
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• pp.1-11
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• 1990

In this study, we will present a knowledge-based consulting system, called THYCONS, for diagnosing thyroid disorders. It has been developed to make the knowledge and expertise of the human expert more widely available, therefore achieving a high-quality diagnosis. Frames will be used to represent the medical knowledge of thyroid disorders, and several rules are attached in each slot of a frame. The uncertainty of diagnostic processes is manipulated by the subjective Bayesian method under the assumption that the pieces of evidence are conditionally independent. Searching for the group of diagnostic tests to be carried out and their optimum sequences will be established in order to infer a more correct diagnosis on the basis of maximum information gain with cost and time restrictions. Additionally. differential diagnosis will be carried out based on the information gained.