• Journal of Advanced Marine Engineering and Technology
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• v.20 no.1
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• pp.13-23
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• 1996

Weld defects degrade the strength and safety of astructure and are resulted from the various cases. The complexity of causal relation of weld defects requires an expert for the analysis of weld defects and the measures counter to them. An expert system has the intelligent functions such as the representation of knowledge and the inference. On this research, weld defect are systematically analysed and their causal model is developed. This information is saved to the knowledge base. The suitable inference algorithm for the diagnosis of weld defects is developed and realized with C++ programming.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.183-190
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• 2012

This study constructs an expert search system which has a mutual cooperation function based on thesis and author profile. The proposed methodology is as follows. First, we propose weighting method which can search a keyword and the most relevant keyword. Second, we propose a method which can search the experts efficiently with this weighting method. On the preferential basis, keywords and author profiles are extracted from the papers, and experts can be searched through this method. This system will be available to many fields of social network. However, this information is distributed to many systems. We propose a method using multi-ontology to integrate distributed data. The multi-ontology is composed of meta ontology, instance ontology, location ontology and association ontology. The association ontology is constructed through analysis of keyword association dynamically. An expert network is constructed using this multi-ontology, and this expert network can search expert through association trace of keyword. The expert network can check the detail area of expertise through the research list which is provided by the system.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.7-11
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• 2013

Taking experts' knowledge to recommend items has shown some promising results in recommender system research. In order to improve the performance of the existing recommendation algorithms, previous researches on expert-based recommender systems have exploited the knowledge of a common expert group for all users. In this paper, we study a problem of identifying personalized experts within a user group, assuming each user needs different kinds and levels of expert help. To demonstrate this idea, we present a framework for using Support Vector Machine (SVM) to find varying expert groups for users; it is shown in an experiment that the proposed SVM approach can identify personalized experts, and that the person-alized expert-based collaborative filtering (CF) can yield better results than k-Nearest Neighbor (kNN) algorithm.

• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.458-467
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• 2016

An expert search method using a large amount of academic data that can provide users with representative research results and advice is required. Since the existing expert search methods perform the expert search based on user profile or activity information, they have a problem that it is hard to discriminate the expert when we do not know the user profile or activity information. In this paper, we propose an academic expert search method using the importance and quality of a paper. The importance of a paper is computed by considering its scarcity and up-to-date topics. The quality of a paper is evaluated by considering the number of citations, IF of Journal, recency and author relations. To show the superiority of the proposed method, we compare it with the existing scheme through the performance evaluation in terms of recall and precision.

• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.73-77
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• 2007

This paper discusses the implementation of a rehabilitation center based on a ubiquitous sensor network. This paper discusses the implementation of a rehabilitation center based on a ubiquitous sensor network. We recognize that certain mild conditions requiring rehabilitation may be treated with minimal human supervision. In place of this constant human supervision, a variety of sensors are used to monitor the patient and rehabilitation progress. These sensors send data through a wireless Zigbee network to a server which stores the data and makes it available to a rehabilitation expert for analysis. This rehabilitation expert also issues rehabilitation prescriptions which are created based on the expert's determination of the patient's condition. By having the ability to control the rehabilitation equipment used, strictly enforce the assigned prescription, and constantly monitor the patient for any warning signs, the system ensures a safe and optimal rehabilitation session.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.355-359
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• 2007

For the decision making of governmental policy about science and technology, domain expert is needed. To choose the expert, the fairness, diversity and speciality is very important. In this research, systematical approach is proposed in the establishment and management of expert database, and recommendation of member of committee for specific field. Additionally, this approach includes the development of tools for the management of governmental committee and the constituents.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.490-492
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• 1998

환경문제를 전혀 야기하지 않으며 하역능률이 뛰어난 차세대 하역설비인 연속식 Unloarder의 하역능률을 관리하고 운전 및 정비의 효율적인 운영을 보장하는 초저가형 Expert System인 SCIS-30과 그 구현에 대하여 소개하고자 한다

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.45-53
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• 1997

This paper presents hybrid expert system for diagnosis of electric power transformer faults. The expert system diagnose and detect faults in oil-filled power transformers based on dissolved gas analysis. As the preprocessing stage, fuzzy information theory is used to manage the uncertainty in transformer fault diagnosis using dissolved gas analysis. The Kohonen neural network takes the interim results by applying fuzzy informations theory as inputs, and performs the transformer fault diagnosis. The Proposed system tested gas records of power transformers from Korea Electric Power Corporation to verify the diagnosis performance of transformer faults.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.65-81
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• 2001

This paper presets the process of knowledge aquisition by partitioning the phase of analysis & design for knowledge-base module construction of Expert System into five steps to derive rule systematically. Also, this paper presents the process and the task that knowledge engineer must do work each step. The knowledge-base module of STAFS expert system was constructed by considering the destruction rate and the commander\`s intention using the proposed rule derivation methodology.