• Korean Journal of Construction Engineering and Management
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• v.6 no.2 s.24
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• pp.92-101
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• 2005

The duration of highrise building projects is more shorter than its increasing of the numbers of floors. The project is liable to overrun of the time in which the project must be complete. AS highrise buildings are increased, time management has been reorganized as critical success factor. To improve time management, time management softwares are introduced and the software's education is made lively in construction company. However a large amount of time management works still have been based on not the software but scheduler's experience. We often can find the time overrun risk of highrise building because of the shortage of scheduler's experience. To diminish the mistake of the scheduler who does not have much experience, we suggested HRB Expert which uses expert's knowledge to make the time plan of highrise building. We made an example of knowledge acquiring and knowledge usage which cased on reinforced concrete work of highrise building by literature review and interview with scheduling expert. The precision of time plan will be enhanced and time overrun will be prevented on condition that HRB Expert is constructed and used

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.568-571
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• 2004

In this study, we propose an efficient expert system (ES) construction mechanism by using dynamic knowledge map (DKM) and database management systems (DBMS). Generally, traditional ES and ES developing tools has some limitations such as, 1) a lot of time to extend the knowledge base (KB), 2) too difficult to change the inference path, 3) inflexible use of inference functions and operators. First, to overcome these limitations, we use DKM in extracting the complex relationships and causal rules from human expert and other knowledge resources. Then, elation database (RDB) and its management systems will help to transform the relationships from diagram to relational table. Therefore, our mechanism can help the ES or KBS (Knowledge-Based Systems) developers in several ways efficiently. In the experiment section, we used medical data to show the efficiency of our mechanism. Experimental results with various disease show that the mechanism is superior in terms of extension ability and flexible inference.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1764-1767
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• 2002

Recent explosive increases in information 'volume have led to a rapid development or a change of information technology which stores, searches, and manages a vast amount of information. It is considered that an effective share and utilization of a large amount of digital information produced by work performances is a pivotal element which can make decisive contributions to a great success of business management. This common property of information reflects a changing social paradigm including a change of business processes. This paper is aimed at designing and embodying the construction of knowledge base in an efficient project management system using unsupervised data mining techniques in order to extract information and utilize it as knowledge about standard data (statistical data, template etc.,), size prediction and a danger precaution notice which are needed for a plan and a scheduling of a new project from data coming from already-established projects.

• Language and Information
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• v.9 no.1
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• pp.19-34
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• 2005

Ontology is an indispensable component in intelligent and semantic processing of knowledge and information, such as in semantic web. However, ontology construction requires vast amount of data collection and arduous efforts in processing these un-structured data. This study proposed a methodology to automatically construct and generate ontologies from Sejong Electronic Dictionary. As Sejong Electronic Dictionary is structured in XML format, it can be processed automatically by computer programmed tools into an OWL(Web Ontology Language)-based ontologies as specified in W3C . This paper presents the process and concrete application of this methodology.

• Computers and Concrete
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• v.23 no.4
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• pp.255-265
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• 2019

The potential of using genetic programming to predict engineering data has caught the attention of researchers in recent years. The present paper utilized weighted genetic programming (WGP), a derivative model of genetic programming (GP), to model the compressive strength of concrete. The calculation results of Abrams' laws, which are used as the design codes for calculating the compressive strength of concrete, were treated as the inputs for the genetic programming model. Therefore, knowledge of the Abrams' laws, which is not a factor of influence on common data-based learning approaches, was considered to be a potential factor affecting genetic programming models. Significant outcomes of this work include: 1) the employed design codes positively affected the prediction accuracy of modeling the compressive strength of concrete; 2) a new equation was suggested to replace the design code for predicting concrete strength; and 3) common data-based learning approaches were evolved into knowledge-based learning approaches using historical data and design codes.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.672-683
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• 2007

The rapid development of Kuala Lumpur has seen numerous new and high-rise buildings introducing Building Automation System (BAS). Whilst effective application of Knowledge Management (KM) within BAS is the pre-requisite for the achievement of optimum BAS performance, there has been little research undertaken to investigate if have been the case. This paper presents a research undertaken to get a view of how KM applies in BAS in six (6) selected case-study buildings in Kuala Lumpur, all operating with the 'one-system' M&E workstation control BAS. The emergent findings positively suggest that adequate KM approaches were employed within their BAS management processes, but further studies would be necessary to determine the extent of their application and effectiveness.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.209-212
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• 2011

Selection of finishing materials in the design stage is an important management factor in terms of use safety and satisfaction, and work cost and process. However, selection of materials in the design stage is usually conducted without related guidelines or a set process, but depends on the experience of the architect or advice of materials company employees. Therefore, the aim of this study was to develop a finishing materials selection process that can be used by a architect. Materials selection related rules collected through interview with experts and five office building cases were used as knowledge. In addition, another aim of the study was to propose a prototype system interface for use in the field.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.764-772
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• 2003

The main thrust of our talk will be based on our experience in developing and applying an attribute-based classification technique in the context of an operational answer set driven retrieval system. To alleviate the difficulty and reduce the cost of manually constructing and maintaining answer sets, i.e., knowledge base, we have devised a new method of automating the answer document selection process by using the notion of attribute-based classification, which is in and of itself novel. We attempt to explain through experiments how helpful the proposed method is for the knowledge base construction process.

• Journal of the Korean Society for Library and Information Science
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• v.34 no.4
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• pp.49-67
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• 2000

The purpose of this study is to suggest knowledge-based digital library model that is applicable in korea university library. This paper provides brief accounts of research and development trends of digital library in referring some major digital library projects that are in progress, or just completed. There follows a suggestion of eight essential modules for knowledge-based digital library system, that are infrastructure development of dissertation presentation and database construction, management and service of collections, infrastructure construction of journal service, development of unified viewer, database conversion, distributed & integrated retrieval system, cyber campus(private work space), and database connection.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.245-252
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• 2022

Risk identification for bridge projects is a knowledge-based and labor-intensive task involving several procedures and stakeholders. Presently, risk information of bridge projects is unstructured and stored in different sources and formats, hindering knowledge sharing, reuse, and automation of the risk identification process. Consequently, there is a need to develop structured and formalized risk information for bridge projects to aid effective risk identification and automation of the risk management processes to ensure project success. This study proposes a semantic risk breakdown structure (SRBS) to support risk identification for bridge projects. SRBS is a searchable hierarchical risk breakdown structure (RBS) developed with python programming language based on a semantic modeling approach. The proposed SRBS for risk identification of bridge projects consists of a 4-level tree structure with 11 categories of risks and 116 potential risks associated with bridge projects. The contributions of this paper are threefold. Firstly, this study fills the gap in knowledge by presenting a formalized risk breakdown structure that could enhance the risk identification of bridge projects. Secondly, the proposed SRBS can assist in the creation of a risk database to support the automation of the risk identification process for bridge projects to reduce manual efforts. Lastly, the proposed SRBS can be used as a risk ontology that could aid the development of an artificial intelligence-based integrated risk management system for construction projects.