• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.764-770
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• 2004

This paper presents a hybrid data mining mechanism to extract expert knowledge from historical data and extend expert systems' reasoning capabilities by using fuzzy neural network (FNN)-based learning & rule extraction algorithm. Our hybrid data mining mechanism is based on association rule extraction mechanism, FNN learning and fuzzy rule extraction algorithm. Most of traditional data mining mechanisms are depended ()n association rule extraction algorithm. However, the basic association rule-based data mining systems has not the learning ability. Therefore, there is a problem to extend the knowledge base adaptively. In addition, sequential patterns of association rules can`t represent the complicate fuzzy logic in real-world. To resolve these problems, we suggest the hybrid data mining mechanism based on association rule-based data mining, FNN learning and fuzzy rule extraction algorithm. Our hybrid data mining mechanism is consisted of four phases. First, we use general association rule mining mechanism to develop an initial rule base. Then, in the second phase, we adopt the FNN learning algorithm to extract the hidden relationships or patterns embedded in the historical data. Third, after the learning of FNN, the fuzzy rule extraction algorithm will be used to extract the implicit knowledge from the FNN. Fourth, we will combine the association rules (initial rule base) and fuzzy rules. Implementation results show that the hybrid data mining mechanism can reflect both association rule-based knowledge extraction and FNN-based knowledge extension.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.235-240
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• 2004

In this paper, we propose a framework for ontological knowledge-based image understanding systems. Ontology composed of concepts can be used as a guide for describing objects from a specific domain of interest and describing relations between objects from different domains The proposed framework consists of four main subparts ⅰ) ontological knowledge bases, ⅱ) primitive feature detectors, ⅲ) concept inference engine, and ⅳ) semantic inference engine. Using ontological knowledge bases on various domains and features extracted from the detectors, concept inference engine infers concepts on regions of interest in an image and semantic inference engine reasons semantic situations between concepts from different domains. We present a outline for ontological knowledge-based image understanding systems and application examples within specific domains such as text recognition and human recognition in order to show the validity of the proposed system.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.222-230
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• 2003

Once the medical knowledge-based system has been developed, it is essential to investigate the knowledge sources of the system because knowledge sources can affect the performance of the system in great deal. This paper presents the method and the results of the reliability test done on the medical knowledge-based system CLINAID. A knowledge source tested is Cardiovascular body system data used in CLINAID. The reliability test will be done by investigating structural relationships revealed by fuzzy relational method between the components of the knowledge sources of individual body systems using syndromes as its main component. These partitions are going to be compared with the syndromes elicited from the medical experts. This paper also reports the outcome of the computations using 7 implication operators performed on Cardiovascular body system data.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.207-219
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• 2004

This paper presents the development of a knowledge-based control system operating via the Internet. With the synergy provided by the Internet, the central expert controller with its knowledge-base has the potential to serve a multitude of front-end clients located anywhere in the world provided they have Internet access. In this way, the operational span of the knowledge-based control system can be expanded to virtually anyplace within the reach of the Internet. This configuration has positive implications in improving the efficiency of distributed operations, thereby enabling plantwide optimization and costs savings. Datasocket technology is adopted to facilitate a more efficient data exchange between the knowledge-based central server and the front-end clients. A specific application in the remote monitoring and fault diagnosis of machines using the proposed control configuration is presented in the paper.

• 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.

• Knowledge Management Research
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• v.14 no.3
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• pp.87-100
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• 2013

As the external knowledge networks of firms have become more and more important to their product and service innovations, many global leading companies such as P & G, IBM, and Samsung Electronics have formulated and implemented their open innovation strategy. This study attempts to empirically analyze the effects of CEOs' supports for external knowledge networks, external knowledge network-oriented cultures and inter-organizational knowledge management systems as the major antecedents to external knowledge networks by using the data based on organizational members' perceptions about them. Based on 847 samples collected from employees in three companies in the medical, the construction and the IT service industries, this study performed a structural equation modeling (SEM) analysis about the effects of the antecedents to the external knowledge networks on product and service innovations through Partial Least Squares (PLS). The empirical findings of this study show that CEOs' supports for external knowledge network positively influence product and service innovations, partially mediated by external knowledge network-oriented cultures and inter-organizational knowledge management systems. And they also show that external knowledge network-oriented cultures and inter-organizational knowledge management systems have a positive effect on product and service innovations, respectively, partially mediated by external knowledge networks. With these new findings, academic and practical implications are discussed.

• Asia pacific journal of information systems
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• v.31 no.3
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• pp.358-377
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• 2021

Knowledge drives business innovation. However, even if companies have the same knowledge element in the business ecosystem, innovation performance varies depending on the structural position of the technical knowledge network. This study investigated whether there is a difference in exploitative innovation according to the structural position of the AI technical knowledge network. We collected patents from the top 100 digital companies registered with the US Patent Office from 2015 to 2019 and classified the companies into knowledge producer-based brokers, knowledge absorber-based brokers, knowledge absorbers, and knowledge producers from the perspective of knowledge creation and flow. The analysis results are as follows. First, a few of the top 100 digital companies disseminate, absorb, and mediate knowledge, while the majority do not. Second, exploitative innovation is the largest, in the order of knowledge producer, knowledge absorber-based broker, knowledge absorber, and knowledge producer-based broker. Finally, patents for industrial intelligence occupy a large proportion, and knowledge producers are leading exploitative innovation. Therefore, latecomers need to expand their resources and capabilities by citing patents owned by leading companies and converge with existing industries into AI-based industries.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.714-719
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• 2005

In this paper, the informative space is proposed to implant ubiquitous functions into physical spaces. We merge physical and virtual spaces through the space structurization using an RFID system, and solve the space localization and mapping problem for a robot to navigate through the distribution and synthesis of information and knowledge. To distribute knowledge flexibly and reliably to changing environment and also to develop a system which allows a robot to invoke and merge the distributed knowledge more freely, we employ a novel approach of knowledge management based on Web services. The proposed method is verified by building a physical space with two kinds of RFID tags and a virtual space with knowledge database based on Web services.

• Information Systems Review
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• v.2 no.2
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• pp.231-244
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• 2000