• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.13-34
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• 1999

Building a knowledge base effectively has been an important research area in the expert systems field. A variety of approaches have been studied including rules, semantic networks, and frames to represent the knowledge base for expert systems. As the size and complexity of the knowledge base get larger and more complicated, the integration of knowledge based with database technology cecomes more important to process the large amount of data. However, relational database management systems show many limitations in handing the complicated human knowledge due to its simple two dimensional table structure. In this paper, we propose Object-Oriented Knowledge Store (OOKS), a knowledge base model on the basis of a frame sturcture using an object-oriented database. In the proposed model, managing rules for inferencing and facts about objects in one uniform structure, knowledge and data can be tightly coupled and the performance of reasoning can be improved. For building a knowledge base, a knowledge script file representing rules and facts is used and the script file is transferred into a frame structure in database systems. Specifically, designing a frame structure in the database model as it is, it can facilitate management and utilization of knowledge in expert systems. To test the appropriateness of the proposed knowledge base model, a prototype system has been developed using a commercial ODBMS called ObjectStore and C++ programming language.

• Korean Journal of Construction Engineering and Management
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• v.2 no.3 s.7
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• pp.83-91
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• 2001

Generally the level of accumulating scheduling knowledge-base in Korean construction companies is in the scheduling knowledge-base infrastructure construction phase and Even in top 10 construction companies, the level is in early scheduling knowledge activity phase. The principle causes of this situation are unawareness of importance to scheduling knowledge and absence of procedure related to scheduling knowledge-base. This research analyzes the problems to accumulate scheduling knowledge-base in Korean construction companies and proposes a procedure model to accumulate scheduling knowledge-base property, which adds items of scheduling knowledge-base infrastructure and scheduling knowledge activity to the existing scheduling procedures of Korean construction companies. Using procedure model for accumulating scheduling knowledge-base, Korean construction companies can develop a new scheduling procedure and accumulate scheduling knowledge accordingly. If scheduling knowledge were accumulated property according to the procedure, a framework for knowledge management system could be provided.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.635-642
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• 2002

There is a rapidly growing demand for the intellectualization of information technology. Especially, in the area of KDD (Knowledge Discovery in Database) which should make an optimal decision of finding knowledge from a large amount of data, the demand is enormous. A large volume of Knowledge Base should be efficiently managed for a more intellectual choice. This study is proposing a Hybrid SOM for an efficient search and renewal of knowledge base, which combines a self-study nerve network, Self-Organization Map with a probable distribution theory in order to get knowledge needed for decision-making management from the Knowledge Base. The efficient knowledge base management through this proposed method is carried out by a stimulation test. This test confirmed that the proposed Hybrid SOM can manage with efficiency Knowledge Base.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.1-7
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• 2011

Most of expert systems use the text-oriented knowledge bases. However, knowledge management using the knowledge bases is considered as a huge burden to the knowledge workers because it includes some troublesome works. It includes chasing and/or checking activities on Consistency, Redundancy, Circulation, and Refinement of the knowledge. In those cases, we consider that they could reduce the burdens by using relational database management systems-based knowledge management infrastructure and convert the knowledge into one of easy forms human can understand. Furthermore they could concentrate on the knowledge itself with the support of the systems. To meet the expectations, in this study, we have tried to develop a general-purposed knowledge conversion tool for expert systems. Especially, this study is focused on the knowledge conversions among text-oriented knowledge base, relational database knowledge base, and decision tree.

• Knowledge Management Research
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• v.10 no.4
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• pp.75-91
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• 2009

Many prior researchers have repeatedly emphasized the importance of utilizing external knowledge as a critical factor for the success of organizational innovation. But they seem to have ignored the importance of the practical methods to advance the ability of finding new way of applying external knowledge to innovation activities. This paper suggests the exploitation of firm's knowledge base in innovative way as a practical method to utilize external knowledge for organizational innovation, because it could be possible to find out a common factor in external knowledge with organizational knowledge base by exploiting it. According to the empirical test with data of 1,143 manufacturing firms, all of the hypothesis were strongly supported.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.211-218
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• 1994

Grinding is considered as a very effective machining technology to attain high production rates and a good surface quality of hard and brittle components. However, the grinding operations till needs the skill and the experience of an operator because of a lack of scientific knowledge and engineering principles. This is the reason why grinding operations are not completley intergrated in CIMS(Computer Intergrated Manufacturing System. Recent develop- ment focus on expert system which deals with domain specific knowledge in order to solve this problem. Firstly, in this study, a basic strategy to develop the grinding knowledge-base for grinding is discussed. Next, the architecture of knowledge-base and management of the grinding knowledge-base(GKB) is described.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.153-156
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• 2005

In this paper, a framework for implementing UFIS (Unified Fuzzy rule-based knowledge Inference System) is presented. First, fuzzy clustering and fuzzy rules deal with the presence of the knowledge in DB (DataBase) and its value is presented with a value between 0 and 1. Second, RDB (Relational DB) and SQL queries provide more flexible functionality fur knowledge management than the conventional non-fuzzy knowledge management systems. Therefore, the obtained fuzzy rules offer the user additional information to be added to the query with the purpose of guiding the search and improving the retrieval in knowledge base and/ or rule base. The framework can be used as DM (Data Mining) and ES (Expert Systems) development and easily integrated with conventional KMS (Knowledge Management Systems) and ES.

• Knowledge Management Research
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• v.1 no.1
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• pp.81-90
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• 2000

This study proposes the knowledge discovery process for the effective mining of knowledge on the web. The proposed knowledge discovery process uses the Prior knowledge base and the Prior knowledge management system to reflect tacit knowledge in addition to explicit knowledge. The prior knowledge management system constructs the prior knowledge base using a fuzzy cognitive map, and defines information to be extracted from the web. In addition, it transforms the extracted information into the form being handled in mining process. Experiments using case-based reasoning and neural network" are performed to verify the usefulness of the proposed model. The experimental results are encouraging and prove the usefulness of the proposed model.

• International Journal of Knowledge Content Development & Technology
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• v.3 no.1
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• pp.81-95
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• 2013

Through a series of precise text handling processes, including automatic extraction of information from documents with knowledge from various fields, recognition of entity names, detection of core topics, analysis of the relations between the extracted information and topics, and automatic inference of new knowledge, the most efficient knowledge base of the relevant field is created, and plans to apply these to the information knowledge management and service are the core requirements necessary for intellectualization of information. In this paper, the knowledge base, which is a necessary core resource and comprehensive technology for intellectualization of science and technology information, is described and the usability of academic information services using it is evaluated. The knowledge base proposed in this article is an amalgamation of information expression and knowledge storage, composed of identifying code systems from terms to documents, by integrating terminologies, word intelligent networks, topic networks, classification systems, and authority data.

• Journal of the Korean Society for information Management
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• v.19 no.1
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• pp.47-69
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• 2002

The concept based retrieval model has shown a higher performance than those of the simple matching function method or the P-norm retrieval method introduced to compensate the demerits of the Boolean retrieval model. However. it takes too long to create a semantic-net knowledge base, which is essential in concept exploration. In order to solve such demerits. a method was sought out by creating a distributed knowledge base by subjects to reduce construction time without hindering the performance of retrieval.