• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.1-6
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• 2003

Associations, as specific forms of knowledge, reflect relationships among items in databases, and have been widely studied in the fields of knowledge discovery and data mining. Recent years have witnessed many efforts on discovering fuzzy associations, aimed at coping with fuzziness in knowledge representation and decision support processes. This paper focuses on associations of three kinds, namely, association rules, functional dependencies and pattern associations, and overviews major fuzzy logic extensions accordingly.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.83-87
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• 2003

Experimental blast studies were carried out in a limestone quarry to study the effects of blasting on structures. To have an in-depth understanding of the possible relation between parameters like vibrations, frequency and scale distance and ten trial blast were conducted. 29 monitoring stations were located in such a pattern to give a true representation of blast induced vibrations for the entire mining in this area. The vibrations were monitored in the vicinity of structures surrounding the quarry in the direction towards the village, road, railway line, office building, etc. Scale distances were determined to identify the maximum charge permissible to cause damage to structures.

• Proceedings of the Safety Management and Science Conference
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• 2000.11a
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• pp.299-306
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• 2000

General definition of data mining is the knowledge discovery or is to extract hidden necessary information from large databases. Its technique can be applied into decision making, prediction, and information analysis through analyzing of relationship and pattern among data. One of the most important work is to find association rules in data mining. The objective of this paper is to find customer's trend using association rule from analysis of database and the result can be used as fundamental data for CRM(Customer Relationship Management). This paper uses Apriori algorithm and FoodMart data in order to find association rules.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.707-713
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• 2003

Convenience and promptness of the internet have been not only making the electronic commerce grow rapidly in case of website, analyzing a navigation pattern of the users has been also making personalization and customization techniques develop rapidly for providing service accordant to individual interestingness. Web personalization and customization skill has been utilizing various methods, such as web log mining to use web log data and web mining to use the transaction of users etc, especially e-CRM analyzing a navigation pattern of the users. In this paper, We measure exact duration time of the users in web page and web site, compute weight about duration time each page, and propose a way to comprehend e-loyalty through the computed weight.

• Computers and Concrete
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• v.26 no.5
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• pp.377-384
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• 2020

A two-dimensional particle flow cod (PFC) is used to study the effect of missile impact on the concrete target. For this purpose firstly calibration of numerical model was performed so that tensile strength of numerical models and experimental sample were the same. Secondly, a concrete model was built. The number of concrete layers and the angle of concrete layers related to horizontal axis were changed. Their numbers were 1, 2, 3 and 4. The angles were 0°, 15°, 30°, 45°, 60°, 75° and 90°. A semi-circle missile was simulated at top of the concrete layers. Its velocity in opposite side of Y direction was 100 m/s. three measuring circles were situated at the below the missile in the model to receive the applied force. The load in the missile and measuring circles together with failure pattern were registered at the beginning of the impaction. The results show that concrete layers number and concrete layers angle have important effect on the failure load while the failure pattern was nearly constant in all of the models.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.199-207
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• 2010

Recently, large amount of information in IDS(Intrusion Detection System) can be un manageable and also be mixed with false prediction error. In this paper, we propose a data mining methodology for IDS, which contains uncertainty based on training process and post-processing analysis additionally. Our system is trained to classify the existing attack for misuse detection, to detect the new attack pattern for anomaly detection, and to define border patter between attack and normal pattern. In experimental results show that our approach improve the performance against existing attacks and new attacks, from 0.62 to 0.84 about 35%.

• Proceedings of the KIEE Conference
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• 2006.07c
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• pp.1535-1537
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• 2006

Recently, the noise discrimination method using PD pulse waveshape analysis has been suggested to be very effective method which can improve the reliability of the on-site PD measurement. In this method, the data clusters due to PD pulses or noises can be distinguished on the PA map. And for the automatic recognition of the PD clusters, it is necessary to adopt the adaptable pattern recognition method. In this study, as for the algorithm which can recognize data clusters, the data mining method has been adopted and the result of the analysis has been reported.

• Smart Structures and Systems
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• v.22 no.6
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• pp.643-662
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• 2018

One of the methods for investigation of mechanical behavior of materials is numerical simulation. For simulation, its need to model behavior is close to real condition. PFC is one of the rock mechanics software that needs calibration for models simulation. The calibration was performed based on simulation of unconfined compression test and Brazilian test. Indeed the micro parameter of models change so that the UCS and Brazilian test results in numerical simulation be close to experimental one. In this paper, the effect of four micro parameters has been investigated on the uniaxial compression test and Brazilian test. These micro parameters are friction angle, Accumulation factor, expansion coefficient and disc distance. The results show that these micro parameters affect the failure pattern in UCS and Brazilian test. Also compressive strength and tensile strength are controlled by failure pattern.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.26-47
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• 2022

Chatbots were an important research subject in the past. A chatbot is a computer program or an artificial intelligence program that participates in a conversation via auditory or textual methods. As the research on chatbots progressed, some important issues regarding them changed over time. Therefore, it is necessary to review the technology with a focus on recent advancements and core research technologies. In this paper, we introduce five different chatbot technologies: natural language processing, pattern matching, semantic web, data mining, and context-aware computer. We also introduce the latest technology for the chatbot researchers to recognize the present situation and channelize it in the right direction.

• Annual Conference of KIPS
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• 2008.05a
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• pp.200-203
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• 2008

최근 전력산업에서의 에너지 가격 및 공급과 수요의 변동, 그리고 기후의 변화에 의해서 부하 예측은 전력회사 경영방침 계획에 있어 중요한 요소가 되었다. 이 논문에서 전력계통의 최적 운용 계획을 위하여 우리가 제안한 기법은 다차원 분석이 가능한 3D 큐브 마이닝과 시간의 변화에 따른 패턴 예측이 가능한 캘린더 기반 시간 데이터 마이닝 기법이다. 이를 통하여 무선 부하 감시 시스템의 부하 데이터의 다차원 분석이 가능하고, 시간 변화에 따른 서로 다른 부하 패턴의 예측이 가능하도록 한다.