• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.233-234
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• 1999

• IE interfaces
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• v.13 no.1
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• pp.37-43
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• 2000

With the rapid changes of business environments and the tremendous amount of information generated from those environments, most companies must learn to manage those changes and information more effectively. Furthermore, within those amounts of information, the information that meets with achieving the goal of each company should be selected and managed as a core competency, i.e. the knowledge, visible and invisible assets of the company. Knowledge management, as a tool of creating, sharing, and applying such knowledge, has pursued those requirements of companies and been studied by many researchers and consultants, especially focusing on the Knowledge Map'. It is said that a knowledge map is a powerful tool for scanning and managing the knowledge that exists in a company and that it is the most important part of establishing a knowledge management base. Until now, however, there have been no specific or practical models for establishing a knowledge map, in spite of the concern. For this reason, this paper suggests a practical model for establishing a knowledge map in terms of a knowledge acquisition procedure based on the traditional research concerning concept maps. In addition to this, for examining the validity of the model, a case study on the 'P' steel and iron company has been performed. This paper's methodology on developing a knowledge map and the procedures to apply them to the real business environment will suggest a cornerstone in the field of practical implementation of knowledge management.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.12-12
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• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

• Korean Journal of Cognitive Science
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• v.3 no.2
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• pp.329-347
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• 1992

This paper deals with the results of development tools for knowldge base implementation on personal computers which is focused on university's student affairs as the education sector.Tje consultant expert system consists of the inference system which makes the object-oriented inference possible by using the present typical rule-based expert systems organized with inference engine,knowledge base,and user interface the user interface management system providing a variety of interfaces,the knowlege managment system for the efficient management and acquirement of knowledge which is independently constucted,and the object management system for the effective management of these systems. This system's design is the consultant expert system'C-I(Consultant-One),in which users can consult with expert at the use's various points of view and which can be operated on the easily accessible personal compuers. We implemented the Student Affairs Administration Consultation Expert System(SACES)'which constructed the knowledge base for three fields of university student affairs management such as timetable management,curriculum and grade points.

• Computers and Concrete
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• v.14 no.6
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• pp.727-743
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• 2014

The management of existing concrete bridges has become a major social concern in many developed countries due to the large number of bridges exhibiting signs of significant deterioration. This problem has increased the demand for effective maintenance and renewal planning. In order to implement an appropriate management procedure for a structure, a wide array of corrective strategies must be evaluated with respect to not only the condition state of each defect but also safety, economy and sustainability. This paper describes a new performance evaluation system for existing concrete bridges. The system evaluates performance based on load carrying capability and durability from the results of a visual inspection and specification data, and describes the necessity of maintenance. It categorizes all girders and slabs as either unsafe, severe deterioration, moderate deterioration, mild deterioration, or safe. The technique employs an expert system with an appropriate knowledge base in the evaluation. A characteristic feature of the system is the use of neural networks to evaluate the performance and facilitate refinement of the knowledge base. The neural network proposed in the present study has the capability to prevent an inference process and knowledge base from becoming a black box. It is very important that the system is capable of detailing how the performance is calculated since the road network represents a huge investment. The effectiveness of the neural network and machine learning method is verified by comparing diagnostic results by bridge experts.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.5
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• pp.442-450
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• 2014

Technology opportunity discovery (TOD) based on technological capability is a process which identifies new product and technology items that can be developed by utilizing or improving a firm's existing products or technologies. By taking into consideration the investment risk of R&D and its practicality, developing technological capability-based TOD methodology is considered to be important for both business and research. To this end, we propose a technological capability-based TOD method and its system using TOD knowledge base. The method can support four types of TOD cases, which are based on a firm's existing technologies and products, and TOD knowledge base is developed by using function information extracted from patent documents. In this paper, we introduce the overall framework of the method and provide application examples on the four TOD cases using the prototype system.

• Journal of the Korean Society for information Management
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• v.26 no.4
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• pp.7-34
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• 2009

Structures of stories, paragraphs, and sentences and inferences applied to indexing and searching were studied to construct the full-text and sentence retrieval system for storytelling. The system designed the database of stories, paragraphs, and sentences and the knowledge-base of inference rules to aid to write the story. The Knowledge-base comprised the files of story frames, paragraph scripts, and sentence logics made by mark-up languages like SWRL etc. able to operate in semantic web. It is necessary to establish more precise indexing language represented the sentences and to create a mark-up languages able to construct more accurate inference rules.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.8
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• pp.357-368
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• 2013

Our society has evolved into a fully connected society in a mixed reality environment enabling various knowledge sharing / management / control / creation due to the expansion of broadband ICT infrastructure, smart devices, cloud services and social media services. Therefore cyber threats have increased with the convenience. The society of the future can cause more complex and subtle problems, if you do not have an effective response to cyber threats, due to fusion of logical space and physical space, organic connection of the smart object and the universalization of fully connected society. In this paper, we propose the strategy to build knowledge-base as the basis to actively respond to new cyber threats caused by future various environmental changes and the universalization of fully connected society.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.271-275
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• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this Purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between $0\∼1$. Second, RDB and SQL(Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS(Knowledge Management Systems)

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.353-359
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• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems (UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between 0 -1. Second, RDB and SQL (Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS (Knowledge Management Systems).