• Knowledge Management Research
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• v.9 no.4
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• pp.65-75
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• 2008

Knowledge workers' workload to register knowledge can cause quality defects in the quality as well as the quantity of knowledge that must be accumulated in a knowledge management system(KMS). To enhance the availability of a KMS by acquiring more quality-guaranteed knowledge, autonomous knowledge acquisition which outdoes the automated acquisition must be initiated. Adopting the capabilities of context-awareness and inference in the field of context-aware computing, this paper intends to autonomously identify and acquire knowledge from knowledge workers' daily lives. Based on knowledge workers' context information, such as location, identification, schedule, etc, a methodology to monitor, sense, and gather knowledge that resides in their ordinary discussions is proposed. Also, a prototype systems of the context-based knowledge acquisition system(CKAS), which autonomously dictates, analyzes, and stores dialogue-based knowledge is introduced to prove the validity of the proposed concepts. This paper's methodology and prototype system can support relieving knowledge workers' burden to manually register knowledge, and hence provide a way to accomplish the goal of knowledge management, efficient and effective management of qualified knowledge.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.37-38
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• 2015

A number of documents containing important and useful knowledge have been generated over time in the construction industry. Such text-based knowledge plays an important role in the construction industry for decision-making and business strategy development by being used as best practice for upcoming projects, delivering lessons learned for better risk management and project control. Thus, practical and usable knowledge creation from construction documents is necessary to improve business efficiency. This study proposes a knowledge creating system from construction documents using text mining and the design comprises three main steps - text mining preprocessing, weight calculation of each term, and visualization. A system prototype was developed as a pilot study of the system design. This study is significant because it validates a knowledge creating system design based on text mining and visualization functionality through the developed system prototype. Automated visualization was found to significantly reduce unnecessary time consumption and energy for processing existing data and reading a range of documents to get to their core, and helped the system to provide an insight into the construction industry.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.145-162
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• 1992

This paper proposes two design principles for expert systems to solve a stock market timing (SMART) problems : machine knowledge and fuzzy post-adjustment, Machine knowledge is derived from past SMART instances by using an inductive learning algorithm. A knowledge-based solution, which can be regarded as a prior SMART strategy, is then obtained on the basis of the machine knowledge. Fuzzy post-adjustment (FPA) refers to a Bayesian-like reasoning, allowing the prior SMART strategy to be revised by the fuzzy evaluation of environmental factors that might effect the SMART strategy. A prototype system, named K-SISS2 (Knowledge-based Stock Investment Support System 2), was implemented using the two design principles and tested for solving the SMART problem that is aimed at choosing the best time to buy or sell stocks. The prototype system worked very well in an actual stock investment situation, illustrating basic ideas and techniques underlying the suggested design principles.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.725-728
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• 2008

According to this plant construction trends, the future plant construction will be very complex, specialization and oversize, so it is expected that future plant construction will create high-profits and require the connection between high-technology and construction method. To catch this advance, more detail business management plan and knowledge sharing technology are needed as basic element. Consequently, this study will analyze the status of current plant industry and develop the educational curriculum for plant business participants, and based on study outcome, this study will propose that web-based portal system by Knowledge Management System(KMS) prototype to fit each company's characteristics.

• Knowledge Management Research
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• v.10 no.1
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• pp.1-15
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• 2009

As pervasive computing technology, which aims to get linked to useful knowledge, information or services anytime, anywhere, using any devices and/or artifacts, is proliferating, desirable impacts on knowledge management systems are now available. The pervasive computing technology will potentially enable the knowledge management systems to realize individualization and socialization and ultimately increase the knowledge processing productivity. However, researchers who apply the pervasive computing methodologies to novel way of knowledge management have been very few. These result in unsatisfactory consideration of establishing pervasive knowledge management systems. Hence, the purpose of this paper is to cast the vision of pervasive knowledge management and search for a couple of possible research issues and possibilities. This paper suggests a framework of ubiDSS, an amended knowledge management system for the next generation deploying pervasive and autonomous knowledge acquisition capabilities of ubiquitous computing technologies. Also the CKAM, context-based knowledge acquisition module, is illustrated as a prototype of future knowledge management systems.

• Korean Management Science Review
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• v.11 no.2
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• pp.65-77
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• 1994

One of the major issues in the implementation and maintenance of CIM databases is the sharing and exchange of information among the heterogeneous databases. This paper addresses some architectural aspects for integrating the heterogeneous multi-databases using knowledge-based expert systems. we propose a loosely integrated coupling system between databases and knowledge-based expert systems. Especially we suggest the architectural aspects of such a coupling methodology. we also present the structure and knowledge representation scheme for the proposed knowledge-based expert system. A prototype example is included to illustrate the framework and its mechanism for implementation.

• International Journal of CAD/CAM
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• v.5 no.1
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• pp.83-90
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• 2005

This is a report on a new methodology to manage design knowledge by utilizing a knowledge-based CAD and a prototype system named $C^3$ (Cubic; CAD knowledge Code Capacitor), which is being developed using our methodology. $C^3$ facilitates (i) the automatic generation of a knowledge code for a knowledge-based CAD by processing design documents written in the format near the natural language, such as English or Japanese, and (ii) automatically generation of a design document written in the format near the natural language from the knowledge code. The features of the system facilitate document-based design knowledge management which reduces the designer's load to encode and maintain design knowledge, because it is easier for a designer to treat a natural language description than a coded description.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.129-147
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• 2005

In Knowledge Management Systems (KMS), tacit knowledge which is usually possessed as forms like know-how, experiences, and etc. is hard to be systemized while managing explicit knowledge is comparatively easy using information technology such as databases, Recent researches in knowledge management have shown that it is more applicable in many ways to provide expert search mechanisms in KMS to pinpoint experts in the organizations with searched expertise so that users can contact them for help, In this paper, we propose an intelligent expert search framework to provide search capabilities for experts in similar or related fields according to the user's needs. In enabling intelligent expert searches, Fuzzy Abstraction Hierarchy (FAH) framework has been adopted, through' which finding experts with similar or related expertise is possible according to the subject field hierarchy defined in the system. To test applicability and practicality of the proposed framework, the prototype system, Knowledge Portal for Researchers in Science and Technology, was developed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.664-667
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• 2000

Although managing knowledge about business processes has been recognized as an important aspect of Knowledge Management System (KMS), it has not been satisfactorily addressed academically or commercially. This paper proposes a KMS architecture to effectively manage business process as knowledge. It expands commonly recognized KMS functions with the process packaging module that defines business processes, monitors and evaluates process instances, keeps process instance history, and provides link between processes and other knowledge items such as documents and experts. The users can not only find the best practice of a business process but also learn from mistakes. A prototype system is implemented to show the feasibility of the proposed architecture. The results of this paper can contribute to expand current KMSs to help use knowledge to enhance the users' performance in their business processes.

• Journal of Korean Society for Quality Management
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• v.18 no.2
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• pp.18-24
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• 1990

The location of inspection stations is a significant component of production systems. In this paper, a prototype expert system is designed for deciding the optimal location of inspection stations. The production system is defined as a single channel of n serial operation stations. The potential inspection station can be located after any of the operation stations. Nonconforming units are generated from a compound binomial distribution with known parameters at any given operation station. Traditionally Dynamic programming, Zero-one integer programming, or Non-linear programming techniques are used to solve this problem. However a problem with these techniques is that the computation time becomes prohibitively large when t be number of potential inspection stations are fifteen or more. An expert system has the potential to solve this problem using a rule-based system to determine the near optimal location of inspection stations. This prototype expert system is divided into a static database, a dynamic database and a knowledge base. Based on defined production systems, the sophisticated rules are generated by the simulator as a part of the knowledge base. A generate-and-test inference mechanism is utilized to search the solution space by applying appropriate symbolic and quantitative rules based on input data. The goal of the system is to determine the location of inspection stations while minimizing total cost.