• Journal of Korea Multimedia Society
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• v.4 no.5
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• pp.465-475
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• 2001

Recent1y, there is growing attention on the researches of inducing association rules from large volume of database. One of them is the method that can be applied to quantitative attribute data. This paper presents a new method for generating large-interval itemsets, which uses locality for partitioning the range of data. This method can minimize the loss of data-inherent characteristics by generating denser large-interval items than other methods. Performance evaluation results show that our new approach is more efficient than previously proposed techniques.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.193-196
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• 2008

네트워크 인프라가 급속히 발전하면서 네트워크 상에서 발생되는 트래픽을 관리하기 위해 마이닝 기법을 적용하려는 여러 연구가 활발히 진행되고 있다. 그러나 기존의 방법들은 DBMS를 이용하여 개개의 플로우를 저장 후 분석하는 방식을 채택함으로써 엄청난 부하와 실시간 마이닝을 어렵게 하는 문제점이 있다. 본 논문에서는 제한된 크기의 메모리를 사용하여 실시간으로 발생하는 네트워크 플로우 데이터 중 빈발한 플로우를 추출하는 방법을 제안한다. 오직 빈발하게 발생하는 플오우만을 메모리에서 모니터링 트리를 사용하여 관리함으로써 메모리를 효율적으로 사용한다. 제안 된 방법은 기존의 방법들과 비교할 때 적은 시스템 부하를 주면서 초고대역폭의 트래픽을 실시간으로 모니터링 할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.471-474
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• 2007

본 논문은 연관규칙탐사 기술에서 사용되는 빈발항목집합과 동일한 개념으로 문서분류의 문서에서 빈발단어집합을 정의하고, 이를 사용하여 문서분류 방법으로 잘 알려진 kNN에 적용하였다. 이를 위하여 하나의 문서는 여러 개의 문단으로 나뉘어졌으며, 각 문단에 나타나는 단어들의 집합을 트랜잭션화하여 빈발단어집합을 찾을 수 있도록 하였다. 제안한 방법은 AI::Categorizer 프레임워크에서 구현되었으며 로이터-21578 데이터를 사용하여 학습문서의 크기에 따라 그 정확도가 측정되었다. 정확도의 측정된 결과로 부터 제안된 방법이 기존의 방법에 비하여 정확도를 개선한다는 사실을 알 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.10-13
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• 2007

모티프는 진화과정을 거치면서 단백질 서열상에서 부분적으로 높게 보존된 지역을 의미한다. 이러한 모티프는 단백질의 기능과 구조를 예측하거나 생물학적으로 관련성이 있는 단백질의 공통적인 특성을 기술하는데 사용된다. 또한, 모티프와 단백질 서열의 상관관계는 생물학적 기능 예측에 필수적이며, 이러한 예측 문제는 모티프 검색을 통해 서열에 존재하는 빈발한 서열패턴과 구조패턴을 통해 단백질 서열에 대한 분석이 가능하다. 이 논문에서는 단백질 서열에 존재하는 2차 구조 특성과 빈발패턴을 검색하고 추출된 정보를 이용하여 단백질 기능 분류에 활용하고자 한다.

• Childhood Kidney Diseases
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• v.5 no.2
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• pp.87-99
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• 2001

Purpose: We studied to find out apo-E genotype polymorphism in minimal change nephrotic syndrome(MCNS) and IgA nephropathy(IgAN) and to determine the relationship between apo-E genotype and clinical course of MCNS. Materials and Method: 43 MCNS patients and 15 IgAN patients were examined for apo-E polymorphism. 50 healthy blood donors were examined for apo-E genotype as control. Genomic DNA was prepared front peripheral blood leukocytes according to standard procedures. Results: As compared with control group, e4 allele frequency was significantly increased in MCNS (p<0.01). However, in IgAN e2 allele frequency, however, was 2.6 times higher than normal control (P<0.01). The frequency of e4 allele of frequent relapser group was 4.6 times higher than normal control and was 2 times higher than infrequent relapser group. Conclusion: We think that apo-E typing might be one of the parameters, which should be considered to predict the course of MCNS in children. MCNS with risky HLA profile and E4/4 genotype could indicate the need for a longer steroid administration. And apo-E genotype needs to be considered for the evaluation of therapeutic responses to other drugs. (J, Korean Soc Pediatr Nephrol 2001 ; 5 : 87-99)

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.125-132
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• 2014

Since frequent pattern mining was proposed in order to search for hidden, useful pattern information from large-scale databases, various types of mining approaches and applications have been researched. Especially, frequent graph pattern mining was suggested to effectively deal with recent data that have been complicated continually, and a variety of efficient graph mining algorithms have been studied. Graph patterns obtained from graph databases have their own importance and characteristics different from one another according to the elements composing them and their lengths. However, traditional frequent graph pattern mining approaches have the limitations that do not consider such problems. That is, the existing methods consider only one minimum support threshold regardless of the lengths of graph patterns extracted from their mining operations and do not use any of the patterns' weight factors; therefore, a large number of actually useless graph patterns may be generated. Small graph patterns with a few vertices and edges tend to be interesting when their weighted supports are relatively high, while large ones with many elements can be useful even if their weighted supports are relatively low. For this reason, we propose a weight-based frequent graph pattern mining algorithm considering length-decreasing support constraints. Comprehensive experimental results provided in this paper show that the proposed method guarantees more outstanding performance compared to a state-of-the-art graph mining algorithm in terms of pattern generation, runtime, and memory usage.

• Journal of Sasang Constitutional Medicine
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• v.8 no.1
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• pp.337-347
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• 1996

The 73 outpatients who had been treated in the Oriental Medical Hospital at Dong Eui Medical Center have participated in this study. The following conclusions were made in comparison with the type of disease and symptom and sasang constitution classification. (in the field of questionnaire analysis) 1. The symptom of "weight loss" is significant differences in sasang constitution classification. The frequency of Taeeum goup is more than Soyang group and Soeum group. 2. The symptom of "vomitig" is significant differences in sasang constitution classification. The frequency of Taeeum goup is more than Soyang group and Soeum group. 3. The symptom of "hoarseness" is significant differences in sasang constitution classification. The frequency of Soeum goup is more than Soyang group and Taeeum group. 4. The symptom of "respiratory distress" is significant differences in sasang constitution classification. The frequency of Taeeum goup is more than Soyang group and Soeum group. 5. The symptom of "arthralgia" is significant differences in sasang constitution classification. The frequency of Soyang goup is more than Taeeum group and Soeum group. 6. The symptom of "menstrual pain" is significant differences in sasang constitution classification. The frequency of Soeum goup is more than Soyang group and Taeeum group. 7. The analysis of past history and sasang constitution classification didn't show any significant differences. Only the analysis of past history and age show significant differences. I think that it is necessary to go deep into the clinical study of the type of disease and symptom according to sasang constitution classification.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.741-754
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• 2008

Due to the characteristics of a data stream, it is very important to confine the memory usage of a data mining process regardless of the amount of information generated in the data stream. For this purpose, this paper proposes the Prime pattern tree(PPT) for finding frequent itemsets over data streams with using the confined memory space. Unlike a prefix tree, a node of a PPT can maintain the information necessary to estimate the current supports of several itemsets together. The length of items in a prime pattern can be reduced the total number of nodes and controlled by split_delta $S_{\delta}$. The size and the accuracy of the PPT is determined by $S_{\delta}$. The accuracy is better as the value of $S_{\delta}$ is smaller since the value of $S_{\delta}$ is large, many itemsets are estimated their frequencies. So it is important to consider trade-off between the size of a PPT and the accuracy of the mining result. Based on this characteristic, the size and the accuracy of the PPT can be flexibly controlled by merging or splitting nodes in a mining process. For finding all frequent itemsets over the data stream, this paper proposes a PPT to replace the role of a prefix tree in the estDec method which was proposed as a previous work. It is efficient to optimize the memory usage for finding frequent itemsets over a data stream in confined memory space. Finally, the performance of the proposed method is analyzed by a series of experiments to identify its various characteristics.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.75-79
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• 2005

최근에 모바일 기기의 급속한 발전과 더불어 다양한 서비스들이 개발되고 있다. 그 중에서도 위치 기반 서비스는 사용자에게 위치와 관련된 유용한 정보를 제공하는 서비스를 말한다. 효과적인 서비스를 제공하기 위해서는 먼저 위치정보를 나타내는 이동 객체 관련기술 연구가 선행되어야 한다. 이러한 연구의 핵심 기술로 현재 빈발한 이동 객체 탐사를 위한 마이닝 기법들에 관한 연구가 진행되고 있다. 본 연구에서는 기존의 수평적 마이닝 기법에서 문제시되었던 많은 후보 이동 객체 발생을 줄이기 위해 새로운 수직적 마이닝 기법을 적용한 방법을 제안한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2017.11a
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• pp.252-253
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• 2017

동일한 작업환경과 작업조건을 가정하였을 때, 사고가 발생할 확률은 작업장에서 일하는 모든 사람들에게 거의 균등하다. 그러나 현실은 다른 사람들과 달리 특정하게 사고를 많이 발생시키는 사고 빈발자가 존재한다. 본 연구는 항해사 인 적성 평가도구를 개발하기 위한 기초단계로 항해사의 운항적성 중 지각 운동 영역에서의 운항적성을 평가하고자 하였다. 항해사의 지각 운동 영역에서의 운항적성 평가를 위해 CBT(Computer-Based Test)의 형태로 항해사의 지각 운동 영역을 측정하고자 하였으며, 지각 운동적 기능이 복합적으로 작용되는 항해의 특성 상 복합적인 측정이 가능한 형태로 검사를 구성하고자 하였다.