• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.125-137
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• 2012

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. For such reason, lots of intrusion detection system has been developed. Intrusion detection system has abilities to detect abnormal behavior and unknown intrusions also it can detect intrusions by using patterns studied from various penetration methods. Various algorithms are studying now such as the statistical method for detecting abnormal behavior, extracting abnormal behavior, and developing patterns that can be expected. Etc. This study using clustering of data mining and association rule analyzes detecting areas based on two models and helps design detection system which detecting abnormal behavior, unknown attack, misuse attack in a large network.

• The Journal of Information Technology
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• v.12 no.3
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• pp.7-17
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• 2009

This research is about the design of an opinion drawing and analysis system through statistical based Web Mining of web contents, where data of opinions are automatically drawn and analyzed concerning web documents that are scattered around in various web sites that exist within the internet. Furthermore, provides a search service that can easily classify positive/negative opinions and also provide searching and statistical information. Users, who want to search for opinions, can input a specific keyword to observe opinions of others easily. In addition, there is a merit in materializing the monitoring system.

• Geomechanics and Engineering
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• v.15 no.1
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• pp.631-643
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• 2018

The estimation of the strength and other mechanical parameters characterizing the tensile behavior of granites can play an important role in civil engineering tasks such as design, construction, rehabilitation and repair of existing structures. The purpose of this paper is to apply data mining techniques, such as multiple regression (MR), artificial neural networks (ANN) and support vector machines (SVM) to estimate the mechanical properties of granites. In a first phase, the mechanical parameters defining the complete tensile behavior are estimated based on the tensile strength. In a second phase, the estimation of the mechanical properties is carried out from different combination of the physical properties (ultrasonic pulse velocity, porosity and density). It was observed that the estimation of the mechanical properties can be optimized by combining different physical properties. Besides, it was seen that artificial neural networks and support vector machines performed better than multiple regression model.

• Journal of the military operations research society of Korea
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• v.24 no.1
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• pp.18-40
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• 1998

This paper is aimed to design an intelligent military decision aiding system in a network computing environment, especially focusing on designing an intelligent analytic system that has data mining tools and inference engine. Through this study, we concluded that the intelligent analytic system can aid military decision making processes. Highlights of the proposed system are as follows : 1) Decision making time can be reduced by the On-line and Real-time analysis ; 2) Intelligent analysis on military decision problems in network computing environments in enabled; 3) The WWW-based implementation models, which provide a standard user interface with seamless information sharing and integration capability and knowledge repository.

• The Journal of Industrial Distribution & Business
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• v.6 no.3
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• pp.5-8
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• 2015

Purpose - This article's aim is to examine how the utilization of existing and future decision-support systems will lead to a change in the auditing process. Research design, data, and methodology - An information system is a special decision-support system that combines information obtained from various sources and communicates among them to help in assessing appropriate complex financial decisions. This paper analyzes techniques such as data and text mining as components of decision-support systems to be used in the auditing process. Results - We present views about how existing decision-support systems will lead to a change in audits. Auditors, who currently collect significant data manually, will in the future move towards management through complex decision-support systems. Conclusions - Although some internal audit functions are integrated into systems of continuous monitoring, the use of such systems remains limited. Thus, instead of multiple decision-support systems, a unified decision-support system can be deployed for this that includes sensors integrated within a company in different contexts (e.g., production, sales, and accounting) that continually monitors violations of controls, unusual patterns, and unusual transactions.

• Korean Management Science Review
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• v.26 no.3
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• pp.101-115
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• 2009

In this paper, we propose a technology mining framework for mobile communication industry. We develop a two phase approach of new technology identification and service enhancement. The new technology identification process consists of R&D issues analysis, technology theme design, and emerging technology sampling. On the other hand, existing service enhancement process has technology landscaping, keyword based search, and technological growth analysis. By implementing these two phase frameworks, we develop a technology portfolio for mobile communication industry.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.2
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• pp.16-32
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• 2002

효율적인 데이타마트 정보의 축척과 질의 정보 추출을 위한 연관 마이닝 방법을 적용하여 검색 속도를 빠르게 할 수 있도록 테이블을 생성하고 고객의 속성별 가중치와 선호기준을 입력받아 선호 점수를 계산하여 점수가 높은 과목을 우선적으로 검색할 수 있도록 기존 연관 알고리즘에서 사용한 단일 항목 입력 데이터 구조를 확장하여 다중 항목 연관 알고리즘(Multiple Item Association Mining : MIAM)을 이용하여 생성된 연관 검색 유형 테이블을 데이터베이스캐시화를 설계하였다. 동일한 알고리즘에서도 데이터베이스캐시 시스템을 적용한 시스템의 질의 처리 수행속도가 우수성을 이용하여 설계함으로써 효율적인 웹 서버 기능을 수행할 수 있음과 동시에 데이터베이스 캐싱의 주요 이점인 효율성 증대, 속도 향상, 비용절감의 효과를 얻을 수 있으므로 연구 설계하였다.

• 한국디지털정책학회:학술대회논문집
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• 2003.12a
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• pp.11-24
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• 2003

It is far more expensive for companies to acquire new customers than it is to retain customers. As a result, companies are turning to Customer Relationship Management (CRM) in order to make decisions about managing the relationship and the profitability of those customer relationships. CRM is a strategy that integrates the concepts of Knowledge Management, Data Mining and Data Warehousing in order to support the organization's decision -making process to retain long-term and profitable relationships with its customers. This paper examines the design implications that CRM poses to data warehousing. We then present a robust data warehouse schema to support CRM analyses and decisions. For example, the proposed schema could be used to calculate customer profitability and to identify social networks of influence between customers. The paper also discusses future areas for research pertaining to CRM data warehousing and data mining.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.1083-1088
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• 2004

Several possibilities on the stability analysis of the railroad tunnels passing through the abandoned mining area are considered in this paper. Previous works on the influence zone due to cavities are investigated to study the effect of the safety deterioration near the cavities which are normally unknown to the engineers. Additional works on the numerical analysis of the influential zone are also performed in 3D space. The praximity of railroad tunnel and unexpected cavities is critical to influence the stability of railroad tunnel under construction. Futhermore, the study on the influence of underground condition like joint and faults should be significantly controlled under both design and construction stage.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.127-134
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• 2016

In this paper, we propose factors that influence on the mobile commerce satisfaction conducted by data mining and a PLS regression analysis. We extracted the most frequent words from mobile application reviews in which there are a large number of user's requests. We employed the content analysis to condense the large number of texts. We took a survey with the categories by which data are condensed and specified as factors that influence on the mobile commerce satisfaction. To avoid multicollinearity, we employed a PLS regression analysis instead of using a multiple regression analysis. Discovered factors that are potential consequences of customer satisfaction from direct requests by customers, the result may be an appropriate indicator for the mobile commerce market to improve its services.