• 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).

• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.57-71
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• 1995

This paper presents a rule extraction algorithm RE to acquire explicit rules from trained neural networks. The validity of extracted rules has been confirmed using 6 different data sets. Based on experimental results, we conclude that extracted rules from RE predict more accurately and robustly than neural networks themselves and rules obtained from an inductive learning algorithm do. Rule extraction algorithm for neural networks are important for incorporating knowledge obtained from trained networks into knowledge based systems. In lieu of this, the proposed RE algorithm contributes to the trend toward developing hybrid and versatile knowledge-based system including expert systems and knowledge-based decision su, pp.rt systems.

• The Journal of Korean Physical Therapy
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• v.24 no.3
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• pp.171-180
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• 2012

Purpose: The purpose of this study was to investigate the clinical decision making (CDM) development process throughout the comparison between novice and expert physical therapist as well as develop a CDM model for physical therapists under the fee-for-service (FFS) and physicians' prescriptions. Methods: Purposive sampling techniques were used to select 10 clinical physical therapists paired into five groups (each pair consisted of 1 novice and 1 expert physical therapist). The coding schemes were extracted from interviews and through within- and across-case analyses, cases were summarized. The reliability of coding schemes was confirmed by checking of case summaries by the participants. Results: Novice and expert physical therapists were influenced by two themes, internalized theme and external forces or information. Novice clinicians depended more on external forces or information. Although clinicians should care patients under the FFS and physician's prescription, expert clinicians were more likely to rely on internalized knowledge. Conclusion: The findings of the present study may be used by educators or association officials enhance CDM abilities and knowledge pools of student or novices as well as develop a guide to suitable novices or students under the specific context limiting the development of their CDM.

• Knowledge Management Research
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• v.19 no.3
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• pp.47-61
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• 2018

A knowledge map, a taxonomy of knowledge repositories, must have capabilities supporting and enhancing knowledge user's activity to search and select proper knowledge for problem-solving. Conventional knowledge maps, however, have been hierarchically categorized, and could not support such activity that must coincide with the user's cognitive process for knowledge utilization. This paper, therefore, aims to verify and develop a methodology to build a networked knowledge map that can support user's activity to search and retrieve proper knowledge based on the referential navigation between content-relevant knowledge. This paper deploys keywords as the semantic information between knowledge, because they can represent the overall contents of a given document, and because they can play the role of semantic information on the link between related documents. By aggregating links between documents, a document network can be formulated: a keyword-based networked knowledge map can be finally built. Domain expert-based validation test was also conducted on a networked knowledge map of 50 research papers, which confirmed the performance of the proposed methodology to be outstanding with respect to the precision and recall.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.91-96
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• 2012

Use of casting simulation software, analyzing the reason for defect became easy. However, to create a practical solution, experienced casting expert's knowledge is always indispensable. In this study, we develop casting design automation system and the algorithm based on casting expert's knowledge, so that faster and more accurate design is enabled. Especially, to generate runner which can be shaped in numerous ways, we suggest the 'nexus' method to shape runner system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.140-145
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• 2008

In this paper, we constructed the advanced cargo monitoring system for liquid cargo tankers which embedded the Decision Support System (DSS) based on the International Ship Management Code (ISM Code). To make this system, we first organized a base of expert's knowledge concerning liquid tanker operations that largely affect ocean accidents. We can find out the knowledge via inference method which simply imitates the fuzzy inference method. Based on this expert's knowledge, we constructed the DSS that provides a code of conduct for operating cargo tanks safely. The proposed monitoring system could eliminate human error when confronting dangerous situations, so the system will help sailors to operate cargo tanks safely.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.284-310
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• 2024

Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.484-487
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• 1992

To resolve the knowledge acquisition bottleneck in the expert systems, the connectionist expert systems have been proposed, which facilitate learning capability of neural networks. This paper is to modify Gallant's connectionist expert network so that it can be applied to more general problems : 1) The hidden nodes are added between the input nodes and an output node, so that the back propagation learning algorithm is used instead of perception based Pocket algorithm. 2) Inference engine is thus modified by modeling that a node may have uncertainties due to unknown inputs.

• Educational Technology International
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• v.11 no.1
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• pp.93-117
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• 2010

The purpose of this study was to develop the problem solving instruction facilitating novice learner to represent the problem. For the purpose, we mainly focused on three aspects of problem solving. First, learner should represent the targeted problem and its solutions for problem solving. Second, from crucial notions of cognitive load theory, learner's mental load should be optimized for problem representation. Third, for optimizing students' mental load, experts may support making their thinking more visible and mapping from their intuition to expert practice. We drew the design principles as follows. First, since providing worked examples for the targeted problem has been considered to minimize analogical errors as well as reduce cognitive load in problem representation at line of problem solving and instructional research, it is needed to elaborate the way of designing. The worked example alternatively corresponds to expert schema that consists of domain knowledge as well as strategies for expert-like problem representation and solution. Thus, it may help learner to represent what the problem is and how to solve it in problem space. Second, principle can be that expert should scaffold learner's self-explanations. Because the students are unable to elicit the rationale from worked example, the expert's triggering scaffold may be critical in that process. The unexplained and incomplete parts of the example should be completed not by expert's scaffold but by themselves. Critical portion of the expert's scaffold is to explain about how to apply and represent the given problem, since students' initial representations may be reached at superficial or passive pattern of example elaboration. Finally, learner's mental model on the designated problem domain should be externalized or visualized for one's reflection as well as expert's scaffolding activities. The visualization helps learner to identify one's partial or incorrect model. The correct model of learner could be constructed by expert's help.

• Proceedings of the Korea Concrete Institute Conference
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• 1995.04a
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• pp.372-377
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• 1995

Expert systems which represent the appllication of artificial intelligence research are now nearly 20 years old. It is said that the present technology together with ever- increasing computing applicability of Combined Hypertext-Expert System Techniques to the design of reinforced concrete structures. Hypertext systems allow the user to control the system while expert systems alone don't give the user any control over the system. Therefore the combination of these two techniques, offered by KnowledgePro, may bring us closer to real user-expert communication. The system developed in this work offers information on design in general by reorganizing ACI Manual 318-89, detailed stress analysis and cross sectional design of simple PC/RC beams and optimum design of reinforced concrete building frames. The system also includes the author's earlier work on guidance to identify types of cracks in concrete. It is also includes the author's earlier work on guidance to identify types of cracks in concrete. It is also demonstrated how well and conveniently existing programs can be used by reorganizing the user manuals in the context of hypertext.