• The Journal of the Korea Contents Association
• /
• v.20 no.3
• /
• pp.223-234
• /
• 2020

This research is the association rule analysis using Apriori algorithm of data mining focusing on 32 predictive key words extracted from Hong (2019) affecting successful aging in Korea. And, to examine rules and patterns of those key words or predictive variables, this research used support, confidence, and lift. The data was analyzed with the R version 3. 5. 1 program, and visualized using arulesViz package and visNetwork. It was found that the variables highly associated with successful aging in Korea were 'hobby', 'volunteer service', 'preparation', and 'exercise'. This research concludes that, the variable which needs to be considered first of all for successful aging in Korea is 'hobby', followed by 'volunteer service', 'preparation', and 'exercise'.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.46 no.6
• /
• pp.7-17
• /
• 2009

The precise analysis of exercise data for designing an effective rehabilitation system is very important as a feedback for planing the next exercising step. Many subjective and reliable research outcomes that were obtained by analysis and evaluation for the human motor ability by various methods of biomechanical experiments have been introduced. Most of them include quantitative analysis based on basic statistical methods, which are not practical enough for application to real clinical problems. In this situation, data mining technology can be a promising approach for clinical decision support system by discovering meaningful hidden rules and patterns from large volume of data obtained from the problem domain. In this research, in order to find relational rules between posture training type and muscle activation pattern, we investigated an application of the WAR(Weishted Association Rule) to the biomechanical data obtained mainly for evaluation of postural control ability. The discovered rules can be used as a quantitative prior knowledge for expert's decision making for rehabilitation plan. The discovered rules can be used as a more qualitative and useful priori knowledge for the rehabilitation and clinical expert's decision-making, and as a index for planning an optimal rehabilitation exercise model for a patient.

• Journal of KIISE:Software and Applications
• /
• v.34 no.1
• /
• pp.40-51
• /
• 2007

To improve academic achievement, the most students not only participate in regular classes but also take various extra programs such as private lessons, private institutes, and educational TV programs. In this paper, we propose a data mining approach to identify which studying methods or usual life patterns during a school vacation affect changes in the academic achievement. First, we derive various studying methods and life patterns that are thought to be affecting changes in the academic achievement during a school vacation. Second, we propose the method of transforming and analyzing data to apply them to decision trees and association rules, which are representative data mining techniques. Third, we construct decision trees and find association rules from the real survey data of middle school students. We have discovered four representative results from the decision trees. First, for students in the higher rank, there is a tendency that private institutes give a positive effect on the academic achievement. Second, for the most students, the Internet teaming sites nay give a negative effect on the achievement. Third, private lessons that have thought to be making a large impact to the achievement, however, do not make a positive effect on the achievement. Fourth, taking several studying methods in parallel nay give a negative effect on the achievement. In association rules, however, we cannot find any meaningful relationships between academic achievement and usual life patterns during a school vacation. We believe that our approach will be very helpful for teachers and parents to give a good direction both in preparing a studying plan and in selecting studying methods during a school vacation.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
• /
• 1995.11a
• /
• pp.91-104
• /
• 1995

본 논문은 UNIX 시스템에서 불법행위를 막을 수 있는 규칙 베이스 전문가 시스템의 설계에 관한 연구이다 먼저 해킹의 유형과 예방 대책에 대한 연구와 아울러 침입 탐지 기법들을 소개하였다. 본 논문에서의 설계된 시스템은 오용 탐지 기법을 적용한 상태전이 분석 침입 탐지의 규칙 베이스 전문가 시스템이다. 기존의 규칙 베이스 시스템이 침입 시나로오에 대한 원시 감사 레코드를 패턴 매칭하는 반면 상태전이 분석 시스템은 상태 변화에 관한 분석에 초점을 둠으로써 시스템의 보안 침해를 받기 직전의 임박한(Impending) 위험에 신속히 대처할 수 있다. 따라서 이러한 분석 기법을 국내에서 개발된 주 전산기 타이컴II의 감사 메카니즘과 연관시켜 규칙 베이스 침입 탐지 시스템을 설계하는 방안을 제시하고자 한다.

• Journal of the Korean Geographical Society
• /
• v.39 no.3
• /
• pp.457-472
• /
• 2004

The purpose of this study is to analyze spatial patterns of traffic accidents and to investigate spatial relations among neighboring spatial objects by applying GIS and spatial data mining methods. This study investigated traffic accident data in Kangnam-gu, Seoul, as a case study. As a result, four clusters were emerged based on individual attributes of traffic accidents. Each cluster showed distinctive properties. In spatial associations between individual attributes of traffic accidents and neighboring spatial objects, there were many rules according to concept hierarchy and definition of spatial relations. Although all rules were not be interesting and significant, they could be a clue to investigate more.

• Proceedings of the Korean Information Science Society Conference
• /
• 2011.06c
• /
• pp.17-20
• /
• 2011

축구 비디오를 분석하고 이를 팀 전략 수립에 활용하는 축구 비디오 분석관의 역할이 강조됨에 따라, 축구 비디오에서 주요 이벤트의 탐지와 같은 절차적 기능에서 부터 고수준의 해석 방법에 이르는 다양한 기능들이 요구된다. 본 논문에서는 축구 웹 캐스트에서 실시간으로 제공하는 텍스트 정보를 기반으로 메타데이터 키워드 매칭을 통하여 축구 경기의 다양한 속성들을 추출하고 텍스트 마이닝의 대표적 해석 기법인 연관규칙 마이닝을 사용함으로써 축구 경기의 전략 수립이 가능한 고수준의 해석 방법을 소개한다. 실제 2010년 월드컵의 스페인 경기를 중계한 웹 캐스트의 텍스트 정보를 대상으로 제안된 방법론의 타당성을 검증한다.

• The KIPS Transactions:PartC
• /
• v.10C no.6
• /
• pp.717-726
• /
• 2003

In this paper, we analyze the associated rule based deductive algorithm which creates the rules automatically for intrusion detection from the vast packet data. Based on the result, we also suggest the deductive algorithm which creates the rules of intrusion pattern fast in order to apply the intrusion detection systems. The deductive algorithm proposed is designed suitable to the concept of clustering which classifies and deletes the large data. This algorithm has direct relation with the method of pattern generation and analyzing module of the intrusion detection system. This can also extend the appication range and increase the detection speed of exiting intrusion detection system as the rule database is constructed for the pattern management of the intrusion detection system. The proposed pattern generation technique of the deductive algorithm is used to the algorithm is used to the algorithm which can be changed by the supporting rate of the data created from the intrusion detection system. Fanally, we analyze the possibility of the speed improvement of the rule generation with the algorithm simulation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.5
• /
• pp.493-498
• /
• 2019

This study deals with the analysis of the technology association rules between CPC codes of the Internet of Things(IoT) patent, the core of the Fourth Industrial Revolution ICT-based technology. The association rules between CPC codes were extracted using R, an open source for data mining. To this end, we analyzed 369 of the 605 patents related to the Internet of Things filed with the Patent Office until July 2019, with a complex CPC code, up to the subclass-level. As a result of the technology association rules, CPC codes with high support were [H04W ${\rightarrow}$ H04L](18.2%), [H04L ${\rightarrow}$ H04W](18.2%), [G06Q ${\rightarrow}$ H04L](17.3%), [H04L ${\rightarrow}$ G06Q](17.3%), [H04W ${\rightarrow}$ G06Q](9.8%), [G06Q ${\rightarrow}$ H04W](9.8%), [G06F ${\rightarrow}$ H04L](7.9%), [H04L ${\rightarrow}$ G06F](7.9%), [G06F ${\rightarrow}$ G06Q](6.2%), [G06Q ${\rightarrow}$ G06F](6.2%). After analyzing the technology interconnection network, the core CPC codes related to technology association rules are G06Q and H04L. The results of this study can be used to predict future patent trends.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.4
• /
• pp.727-736
• /
• 2014

The fundamental concerns of this paper are to analyze the effects of some characteristics on the employment of new college graduated students in viewpoint of data visualization. We use individual and department characteristic data of K-university graduated students in 2010. We apply multiple correspondence analysis, decision tree analysis, association rules and social network analysis for data visualization. The results of the analysis are summarized as follows. First, an analysis of the determinants of employment shows that GPA, department category, age and number of majors, recruiting time affect the employment rate. Second, higher GPA and natural category of department positively affect the employment rate. Finally, low age, single major and early recruiting time also positively affect the employment rate.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2004.05a
• /
• pp.557-560
• /
• 2004

추천 시스템에서부터 1:1 마케팅에 이르는 전자 상거래의 다양한 응용 영역에서, 개별 사용자로부터 개인화된 사용자 프로파일을 구축하는 것은 매우 중요하다. 이러한 프로파일들은 사용자들의 구매 행위와 같은 개인별 행동들을 설명해주며, 특히 다양한 데이터 마이닝(Data Mining) 기술들을 이용해 사용자의 거래 기록으로부터 학습된 규칙들을 발견해낼 수 있다. 발견된 규칙들 중에는 거짓이거나 연관 없거나 또는 하찮은 것들도 존재하기 때문에, 가장 중요한 문제 가운데 하나는 발견된 규칙들을 처리후-분석을 어떻게 수행하느냐이다. 예를 들어, 발견된 규칙을 사용자 프로파일에 적합한 것인지를 확인할 때 좋은 규칙과 나쁜 규칙을 어떻게 판명하는가 하는 문제이다. 이 논문에서는 규칙을 확인하는 과정에서 객관적 척도를 이용하는 방법을 제안하였다.