• IE interfaces
• /
• v.2 no.2
• /
• pp.51-62
• /
• 1989

A computer-aided simulation modeling system has been developed to allow the automatic construction of complete discrete simulation models for queueing systems. Three types of knowledge are used in the specification and construction of a simulation modeling: Knowledge of queueing system, simulation modeling, and a target simulation language. This knowledge has been incorporated into the underlying rule base in the form of extraction and construction rule, and implemented via the expert system building tool, OPS5. This paper suggested a knowledge based approach for automatic programming to enable a user who lacks modeling knowledge and simulation language expertize to quickly build executable models.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.4
• /
• pp.55-62
• /
• 2016

In this paper, we propose the INDEM(Internet News Data Extraction Middleware) system for the removal of the unnecessary data in internet news. Although data on the internet can be used in various fields such as source of data of IR(Information Retrieval), Data mining and knowledge information service, it contains a lot of unnecessary information. The removal of the unnecessary data is a problem to be solved prior to the study of the knowledge-based information service that is based on the data of the web page. The INDEM system parses html and explores the XPath, and it is to perform the analysis. The user simply utilize INDEM by implementing an abstract class that provides INDEM, and can obtain the analysis information. INDEM System through this process delivers the analysis information including the main contents of news site to the users. In this paper, the INDEM system was adapted in a stand-alone and web service system and it was evaluated on the basis of 16 news site. As a result, performance of the INDEM system is affected in html source data size and complexity of used html grammar than the main news data size.

• The Journal of Society for e-Business Studies
• /
• v.3 no.2
• /
• pp.57-71
• /
• 1998

In this paper, we describe the approaches of shopping agents and directory services for online comparison shopping on the web, and propose an information indexing and retrieval system, named InfoEye, with a new method for automatic extraction of product information. The developed method is based on the knowledge about presentation of the product information on the Web. The method from the knowledge about presentation of the product information is derived from both the point that online stores display their products to customers in easy-to-browse ways and heuristics made of analyses of product information look-and-feel of domestic online stores. In indexing process, the method is applied to product information extraction from Hypertext Markup Language (HTML) documents collected by a mirroring robot from online stores. We have made InfoEye to a readily usable stage and transferred the technology to Webnara commercial shopping engine. The proposed system is a cutting-edge solution to help customers as a shopping expert by providing information about the reasonable price of a product from dozens of online stores, saving customers shopping time, giving information about new products, and comparing quality factors of products in a same category.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.3
• /
• pp.372-381
• /
• 2006

The purpose of this study was to develop a process management system to manage ingot fabrication and improve ingot quality. The ingot is the first manufactured material of wafers. Trace parameters were collected on-line but measurement parameters were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Therefore, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were used for data generation. Then, modeling was performed, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to control parameters. Secondly, rule extraction was performed to find the relation between the production quality and control conditions. The extracted rules can give important information concerning how to handle the process correctly. The dynamic polynomial neural network (DPNN) and decision tree were applied for data modeling and rule extraction, respectively, from the ingot fabrication data.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.9 no.3
• /
• pp.61-67
• /
• 2009

The proliferation of the Internet grows, according to electronic documents, along with increasing importance of technology in information retrieval. This research is possible to build a more efficient and accurate knowledge-base with unstructured text documents from the Web using to extract knowledge of the core meaning of LGG (Local Grammar Graph). We have built a ontology based on OWL(Web Ontology Language) using the areas of particular stocks up/down patterns created by the extraction and grammar patterns. It is possible for the user can search for meaning and quality of information about the user wants.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.6
• /
• pp.17-26
• /
• 2009

In national defense, established information systems are mainly based on simple information processing, such as mass data query. They have thus lacked intelligent ability of information and knowledge representation ability. We therefore need the research about the construction of military ontology which is the main topic for knowledge construction. Military ontology can help us develop the intelligent national defense information system which can search and manage information efficiently. In this paper, we present the six-step bottom-up approach for military ontology extraction, then we apply this approach to one of military domain, called national defense educational training, and finally implement it using $Prot\acute{e}g\acute{e}$ which is one of the most useful ontology development tool.

• The Journal of the Korean dental association
• /
• v.57 no.6
• /
• pp.326-332
• /
• 2019

Extraction treatment has been used for a long time to treat crowding or lip protrusion patients and still extraction decision is the most difficult and important decision during diagnosis and treatment planning. If the amount of crowidng is severe, premolar extraction is often considered. Because of their location, premolar extractions would seem to allow for the most straightforward relief of crowding and the improvement of soft tissue profile. But patients and their parents often prefer nonextraction approach if possible and such a preference gives us serious question about the boundary of nonextraction treatment. Because Orthodontic Mini-Implant (OMI) become popular these days, distalization of posterior teeth can be obtained easily without patient's compliance. For this reason, many orthodontists are trying to treat crowding patient with nonextraction than before. But sometime, unexpected side effects are observed including unesthetic profile, impaction of second molar and long treatment time. All the tools for space gaining - extraction, arch expansion, molar distalization and interproximal enamel reduction - have their limitations and indications. Possible side effects and limitations should be carefully considered during the treatment planning. Although Korean patients usually require extraction more often than US or European patients, more knowledge about the tools for space gaining would help us to decrease the rate of extraction and the problems during treatment of crowding patients.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
• /
• 1998.04a
• /
• pp.314-320
• /
• 1998

Wear debris morphology is closely related to the wear mode and mechanism occured. Image recognition of wear debris is, therefore, a powerful tool in wear monitoring. But it has usually required expert's experience and the results could be too subjective. Development of automatic tools for wear debris recognition is needed to solve this problem. In this work, an algorithm for automatic wear debris recognition was suggested and implemented by PC base software. The presented method defined a characteristic 3-dimensional feature space where typical types of wear debris were separately located by the knowledge-based system and compared the similarity of object wear debris concerned. The 3-dimensional feature space was obtained from multiple feature vectors by using a multi-dimensional scaling technique. The results showed that the presented automatic wear debris recognition was satisfactory in many cases application.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2003.05a
• /
• pp.884-888
• /
• 2003

In this paper, we introduce the hybrid data mining mechanism based in association rule and fuzzy neural networks (FNN). Most of data mining mechanisms are depended in the association rule extraction algorithm. However, the basic association rule-based data mining has not the learning ability. In addition, sequential patterns of association rules could not represent the complicate fuzzy logic. To resolve these problems, we suggest the hybrid mechanism using association rule-based data mining, and fuzzy neural networks. Our hybrid data mining mechanism was consisted of four phases. First, we used general association rule mining mechanism to develop the initial rule-base. Then, in the second phase, we used the fuzzy neural networks to learn the past historical patterns embedded in the database. Third, fuzzy rule extraction algorithm was used to extract the implicit knowledge from the FNN. Fourth, we combine the association knowledge base and fuzzy rules. Our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.12
• /
• pp.35-48
• /
• 2017

Extracting temporal information from documents is becoming more important, because it can be used to various applications such as Question-Answering (QA) systems, Recommendation systems, or Information Retrieval (IR) systems. Most previous studies only focus on English documents, and they are not applicable to the other languages due to the inherent characteristics of languages. In this paper, we propose a new system, named ExoTime, designed to extract temporal information from Korean documents. The ExoTime adopts an external Knowledge Base (KB) in order to achieve better prediction performance, and it also applies a bagging method to the temporal relation prediction. We show that the effectiveness of the proposed approaches by empirical results using Korean TimeBank. The ExoTime system works as a part of ExoBrain that is an artificial intelligent QA system.