• Korean Management Science Review
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• v.12 no.3
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• pp.135-161
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• 1995

This paper is concerned with a conceptual design of a knowledge-based modeler for network analysis. The "knowledge-based modeler" approach is suggested as a method for incorporating the user's qualitative knowledge and subjective decison in the course of the mathematical modeling and the subsequent solution procedure. The submodules of the proposed modeler such as database, model/algorithm base and functional knowledge bases are identified and the flows of information between the submodules are sequentially defined. A prototype system is implemented for experimental purpose by using the application software GURU.ware GURU.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.431-434
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• 2001

Knowledge discovery in databases(KDD) is the process for extracting valid, novel, potentially useful and understandable knowledge form real data. There are many academic and industrial activities with new technologies and application areas. Particularly, data mining is the core step in the KDD process, consisting of many algorithms to perform clustering, pattern recognition and rule induction functions. The main goal of these algorithms is prediction and description. Prediction means the assessment of unknown variables. Description is concerned with providing understandable results in a compatible format to human users. We introduce an efficient data mining algorithm considering predictive and descriptive capability. Reasonable pattern is derived from real world data by a revised neural network model and a proposed fuzzy rule extraction technique is applied to obtain understandable knowledge. The proposed neural network model is a hierarchical self-organizing system. The rule base is compatible to decision makers perception because the generated fuzzy rule set reflects the human information process. Results from real world application are analyzed to evaluate the system\`s performance.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.99-106
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• 1998

In this paper, we have constructed an expert system for semiconductor chip encapsulation which combines a knowledge-based system with CAE software. The knowledge-base module includes heuristic and pre analysis knowledge for evaluation and redesign. Evaluation of the initial design and generation of redesign recommendations can be developed from the rules as applied to a given chip package. The CAE programs can be used for simulating the filling and packing stage of encapsulation process. The expert system is a new tool which enables package design or process conditions with high yields and high productivity.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.983-987
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• 2001

This paper deals with an automated computer-aided process planning system by which designer can determine operation sequences even if they have little experience in process planning of wheel bolt products by a multi-stage former. The approach to the system is based on knowledge-based rules and a process knowledge base consisting of design rules is built. Knowledge for the system is formulated from plasticity theories, empirical results and the empirical knowledge of field experts. Programs for the system have been written in AutoLISP for the AutoCAD using a personal computer and are composed of two main modules. An attempt is made to link programs incorporationg a number of expert design rules to form a useful package. Results obtained using the modules enable the designer and manufacturer of wheel bolt product to be more efficient in this field.

• The Journal of Society for e-Business Studies
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• v.7 no.1
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• pp.75-86
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• 2002

In this study, we proposed design issues and structure of a web mining system and develop a system for the purpose of knowledge integration under world wide web environments resulted from our developing experiences. The developed system consists of three main functions： 1) gathering documents utilizing a search agent; 2) determining similarity coefficients between any two documents from term frequencies; 3) clustering documents based on similarity coefficients. It is believed that the developed system can be utilized for discovery of knowledge in relatively narrow domains such as news classification, index term generation in knowledge management.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.271-277
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• 2013

Typical semantic search query for Semantic search promises to provide more accurate result than present-day keyword matching-based search by using the knowledge base represented logically. Existing keyword-based retrieval system is Preference for the semantic interpretation of a user's query is not the meaning of the user keywords of interconnect, you can not search. In this paper, we propose a method that can provide accurate results to meet the user's search intent to user preference based evaluation by ranking search. The proposed scheme is Integrated ontology-based knowledge base built on the formal structure of the semantic interpretation process based on ontology knowledge base 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.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1887-1891
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• 2005

Despite significant advances in multimedia transferring technologies in various fields of robotics, it is sometimes quite difficult for the operator to fully understand the context of 3D remote environments from 2D image feedback. Particularly, in the remote control of mobile robots, the recognition of the object associated with the task is very important, because the operator has to control the robot safely in various situations not through trial and error. Therefore, it is necessary to provide the operator with 3D volumetric models of the object and object-related information as well such as locations, shape, size, material properties, and so on. Thus, in this paper, we propose a vision-based human interface system that provides an interactive, information-rich map through network-based information brokering. The system consists of an object recognition part, a 3D map building part, a networked knowledge base part, and a control part of the mobile robot.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.970-973
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• 1995

The proposal of this paper is the constructing of knowledge database with manufacturing information. This database contains characteristics of workpiece materials, cutting tools, NC machines, manufacturing processes, and work conditions. And all shape in the system are feature models such base plate, step, hole, pocket, boss, and slot. These information generate a final decision for machining process by the expert system.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3010-3022
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• 1997

Expert system is one of AI area which was came out at the end of 19705s. It simulates the human's way of thinking to give solutions of Problem in many applications. Most expert system consists of many components such as inference engine, knowledge base, and so on. Especially the performance of expert system depends on the control of enfficiency of inference engine. Inference engine has to get features; tirst, if possible to minimize restrictions when the knowledge base is constructed second, it has to serve various kinds of inferencing methods. In this paper, we design and implement the inference engine which is able to support the general functions to knowledge domain and inferencing method. For the purpose, forward chaining, backward chaining, and direct chaining was employed as an inferencing method in order to be able to be used by user request selectively. Also we not on1y selected production system which makes one ease staradization and modulation to obtain knowledges in target domain, but also constructed knowledge base by means of Extended Clause Bit Metrics (ECBM). Finally, the performance evaluation of inference engine between Rete pattern matching and ECBM has been done.