• The Korean Journal of Applied Statistics
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• v.5 no.2
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• pp.211-227
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• 1992

In this paper we consider the definition and mathematical properties of similarity or dissimilarity which have often used in clust analysis, and we apply a hierarchical agglomerative cluster algorithm to a dissimilarity metrx generated by these distance. Here we investigate the effect of relation between distance function and cluster algorithm on the retrieval ability of natural clusters. We present an empirical results for qualitative data as well as quantitative data.

• Journal of KIISE:Databases
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• v.33 no.5
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• pp.463-475
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• 2006

In applications such as a traffic management system, analysis using a spatial hierarchy of a spatial data warehouse and a simple aggregation is required. Over the past few years, several studies have been made on solution using a spatial index. Many studies have focused on using extended R-tree. But, because it just provides either the current aggregation or the total aggregation, decision support of traffic policy required historical analysis can not be provided. This paper proposes hybrid index based on extended aR-tree for the spatio-temporal aggregation. The proposed method supports a spatial hierarchy and the current aggregation by the R-tree. The sorted hash table using the time structure of the extended aR-tree provides a temporal hierarchy and a historical aggregation. Therefore, the proposed method supports an efficient decision support with spatio-temporal analysis and is Possible currently traffic analysis and determination of a traffic policy with historical analysis.

• Journal of Digital Contents Society
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• v.14 no.4
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• pp.401-410
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• 2013

A big success of the 3D film 'Avatar' in 2009 opened a full-fledged 3D movie era. A new industrial possibility of 3D contents was predicted in Korea and then the support for 3D contents production took placed via various media platforms. Korean government also announced the new development policies with a focus on 3D content. However, the 3D content industry has not been activated. Therefore, in this study by applying AHP(Analytic Hierarchy Process) method we tried to grasp the reason of the deactivation of 3D content industry through analyzing the relative importance rate of three research factors(content aspects, technical aspects, and policy aspects) that were mainly considered to activate the industry. The results of this study showed that the relative importance rate of content aspects was higher than that of technical aspects and policy aspects. It means the lack of 3D contents is one of main reason causing the delay of 3D industrial activation. And it also showed that the relief of human factors such as visual fatigue evaluated as a sub-factors of technical aspects are challenges to be solved soon..

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.135-145
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• 2017

Principal component analysis (PCA) describes the variation of multivariate data in terms of a set of uncorrelated variables. Since each principal component is a linear combination of all variables and the loadings are typically non-zero, it is difficult to interpret the derived principal components. Sparse principal component analysis (SPCA) is a specialized technique using the elastic net penalty function to produce sparse loadings in principal component analysis. When data are structured by groups of variables, it is desirable to select variables in a grouped manner. In this paper, we propose a new PCA method to improve variable selection performance when variables are grouped, which not only selects important groups but also removes unimportant variables within identified groups. To incorporate group information into model fitting, we consider a hierarchical lasso penalty instead of the elastic net penalty in SPCA. Real data analyses demonstrate the performance and usefulness of the proposed method.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06d
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• pp.373-376
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• 2008

현재의 인터넷은 새로운 기술적 요구를 수용하기에 어려운 단계에 이르러 마침내 현 인터넷과의 호환성을 완전히 배제한 새로운 네트워크를 설계하려는 미래네트워크 또는 미래 인터넷 연구가 진행되고 있다. 가상화 기술 기반의 네트워크는 다양한 네트워크 요구사항을 충족하는 네트워크들이 overlay로 공존할 수 있으며, 요구사항의 변화로 인해 완전히 새로운 접근방법이 필요한 경우에도 가상화 기반의 네트워크를 통해 수용이 가능한 장점이 있다. 본 논문에서는 미래인터넷의 핵심 개념인 인프라스트럭처 가상화에 대하여 관련 연구동향을 분석한다. 그리고 이를 기초로 미래네트워크 구조를 제시한다. 가상화된 인프라 기반의 미래네트워크 구조를 3계층 - 서비스 조합 및 연합 계층, 정책 및 제어 계층, 패킷 처리 계층 - 으로 제시하고 각 계층별 기능을 설명한다.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.121-129
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• 2016

The purpose of this study is to set a standard for sale prices of supplying apartment houses about decision factors in sale price of supplying apartment houses using Analytic Hierarchy Process. This is done by modeling decision factors in sale price of supplying apartment houses as hierarchy. According to the modeled hierarchy, the relative importance of supplying factors are determined using a survey of a group of real estate experts. In addition, through Analytic Hierarchy Process, the relative importance of phased sale prices of supplying apartment is analyzed in order to set a standard to estimate competitive sale prices of newly supplying apartment houses.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.565-572
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• 2019

Optimization of production system of polyester manufacturing companies is an important task for strengthening the competitiveness of the domestic polyester industry. The purpose of this study is to present a way to evaluate the goodness of the polyester manufacturing systems determined by the combinations of production facilities and to derive the optimal configuration of the production system. To this end, the criteria or factors for the evaluating polyester production system were derived and the Analytic Hierarchy Process (AHP) was used. Using the AHP model, we derived weights on the criteria for evaluating polyester production system and drew priorities for the configurations of the production systems under consideration.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.393-396
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• 2002

최근 대용량의 데이터베이스로부터 유용한 정보를 발견하고 데이터간에 존재하는 연관성을 탐색하고 분석하는 데이터 마이닝에 관한 많은 연구들이 진행되고 있다. 실제 응용분야에선 수집된 데이터는 시간이 지날수록 데이터의 양이 늘어나게 되고, 중복되는 속성과 잡음을 갖게 되어 마이닝 기법을 이용하는데 많은 시간과 비용이 소요된다. 또한 어느 속성이 중요한지 알 수 없어 중요한 속성이 중요하지 않은 속성에 의해 왜곡되거나 제대로 분석되지 않을 수 있다. 본 연구는 이러한 문제점들을 해결하기 위해 GHSOM을 이용한 계층적 신경망 군집화 방법을 제안한다. 제안하는 방법은 비리 군집의 개수를 정해줄 필요가 없고, 다양한 레벨의 군집들을 얻을 수 있는 계층적 군집화를 이루어낸다는 장점을 갖는다. 본 논문에서는 신경망 GHSOM의 구조와 특성에 대해 간략히 살펴보고 시스템 처리과정에 대해 설명한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.9
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• pp.746-752
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• 2012

SVC layered video is consists of a Base Layer (BL) and Enhancement Layer (EL). Without the base layer decoding, the higher EL layer can not be decoded. Therefore, successful transfer of the BL is important factor for improving the SVC video data. In this paper, we propose a network coding of layered video to improve success decoding probability with the importance order of the video data over a multi-relay system. We shows that formula analysis and experimental results of the proposed network coding scheme. In addition, we shows performance of video quality according to the number of relays.

• Journal of the Korean Society for Library and Information Science
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• v.38 no.4
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• pp.179-192
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• 2004

In this paper, we present that the result of document clustering can change dramatically with respect to the different ways of indexing compound nouns. First of all, the automatic indexing engine specialized for Korean words analysis, which also serves as the backbone engine for automatic document clustering system, is introduced. Then, the details of hierarchical agglomerative clustering(HAC) method, one of the widely used clustering methodologies in these days, was illustrated. As the result of observing the experiments, carried out in the final part of this paper, it comes to the conclusion that the various modes of indexing compound nouns have an effect on the outcome of HAC.