• Journal of Information Technology Applications and Management
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• v.12 no.3
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• pp.41-56
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• 2005

Product recommender system is one of the most popular techniques for customer relationship management. In addition, collaborative filtering (CF) has been known to be one of the most successful recommendation techniques in product recommender systems. However, CF has some limitations such as sparsity and scalability problems. This study proposes hybrid cluster analysis and case-based reasoning (CBR) to address these problems. CBR may relieve the sparsity problem because it recommends products using customer profile and transaction data, but it may still give rise to scalability problem. Thus, this study uses cluster analysis to reduce search space prior to CBR for scalability Problem. For cluster analysis, this study employs hybrid genetic and K-Means algorithms to avoid possibility of convergence in local minima of typical cluster analyses. This study also develops a Web-based prototype system to test the superiority of the proposed model.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.105-112
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• 2019

In this paper, we propose a technique to analyze similarity between SQL queries and to assist integrating similar tables. First, the table information was extracted from the SQL queries through the query structure analyzer, and the similarity between the tables was measured using the Jacquard index technique. Then, similar table clusters are generated through hierarchical cluster analysis method and the co-occurence probability of the table used in the query is calculated. The possibility of integrating similar tables is classified by using the possibility of co-occurence of similarity table and table, and classifying them into an integrable cluster, a cluster requiring expert review, and a cluster with low integration possibility. This technique analyzes the SQL query in practice and analyse the possibility of table integration independent of the existing business, so that the existing schema can be effectively reconstructed without interruption of work or additional cost.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.437-442
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• 2020

Since the advent of the innovative information technology called the Internet, the dynamism of the information environment has brought about changes in information users' needs and behavior. It is essential to understand information users in this rapidly changing environment, and based on this, it is necessary to effectively build and operate an information service and a system therefor. The purpose of this study is to understand the characteristics according to the segmentation of users of the National Science and Technology Information Service System, and to derive improvements to customized services and content development through research and analysis of content usage. A total of 816 science and technology information service system users participated in online surveys from September to November. Collected data is applied to factor analysis and cluster analysis techniques to subdivide users of science and technology information service systems, to recognize new information technologies and information services, science technology information needs, and science and technology attributes that users consider important. We derived the results according to the segmented user group.

• Bulletin of the Korean Chemical Society
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• v.3 no.2
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• pp.50-55
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• 1982

A study of small water clusters composed of two to seven molecules has been performed by using the revised empirical potential function for conformational analysis (REPFCA). Various structures of clusters have been investigated and the relative probability of cluster per molecule is discussed. In general, cyclic structures of water clusters are more favorable than open structures. It is found that cyclic pentamer is the most favorable unit structure in the water cluster.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.4
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• pp.1-16
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• 2023

The purpose of this study is to understand the vegetation structure of the Corylopsis coreana habitats in South Korea and their correlation with environmental factors, in order to provide basic data for preparing conservation. A total of 40 vegetation survey plots were established in around Southern region, Gangwon-do and Gyeonggi-do Province. The cluster analysis revealed four distinct clusters: Quercus mongolica-Pinus densiflora (QmPd), Castanea crenata (Cc), Quercus mongolica (Qm), and Pinus koraiensis (Pk). Among them, the QmPd cluster was selected as the representative community. Soil texture analysis that most areas consisted of loamy soil and were distributed on the northern aspects. The plantation, represented by Pk, exhibited a high content of exchangeable aluminum (5.227±0.342 mg/kg), suggesting the need for soil improvement and monitoring in these habitats. The canopy openness (forest gap) ranged from 11% to 21%, indicating a relatively closed canopy in many survey plots. Non-metric multidimensional scaling analysis indicated heterogeneous species composition between the QmPd cluster and the Pk cluster (total R² = 0.608).

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.1
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• pp.90-100
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• 1999

유전자 알고리즘은 전통적인 등반 알고리즘을 이용하여 구하기 어려웠던 최적화 문제를 해결하기 위한 강인한(Robust) 탐색 기법이다. 특히 목적함수가 (1)여러 개의 국부 최대치를 가지는 경우, (2)수학적으로 표현이 불가능하거나 어려운 경우, (3)목적함수에 교란 항(disturbance term)이 섞여 있을 경우도 우수한 탐색 능력을 갖는 것으로 알려져 있다. 본 논문에서는 유전자 알고리즘을 이용하여 나타나는 다양한 해집합을 형성하는 개체군을 군집성 분석(cluster analysis)을 이용하여 군집화하고, 각 군집에 부여된 군집 적합도에 따라서 최적해를 구함으로써 단순 유전자 알고리즘에 의한 최적화보다 훨씬 향상된 탐색 알고리즘을 제안하였다. 반응표면의 형태가 정형화한 테스트 함수의 형태로 나타난다고 가정한 경우에 대하여 몬테 칼로 시뮬레이션을 통하여 본 알고리즘을 적용하여 평가하고 분석하였다.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.547-549
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• 2007

Recently with increasing the use of parallel computing and cluster system which was connected high speed network, the interest about distributed and parallel file system is increasing. Specially, there are many researches, which focused on optimizing the performance of distributed and parallel file system for the more efficient use of cluster system. In this paper, we analyzed the performance of PVFS(Parallel Virtual File System) in small cluster system. In addition, to improve the PVFS performance we proposed the chancing the size of flow buffer according to the network speed and we optimized the PVFS performance on small cluster system.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.241-248
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• 2002

An electronic noses system including six metal oxide sensors was used to predict the characteristics of shelf-life of soybean curd. Soybean curd was stored at two different temperatures defined as low temperature(5$\^{C}$) and high temperature(25$\^{C}$). Resistance changes of the sensors were measured 13 times for 19 days at low temperature and 19 times for 120 hours at high temperature. Three different analytical methods such as graphical analysis(GA), principal component analysis(PCA), and cluster analysis(CA) were used to analyze sensors outputs. The ratio of resistance was decreased according to increasement of shelf-life. Using PCA it was possible to predict freshness and shelf-life time of soybean curds. Also, using CA it was possible to simplify an electronic nose system. Electronic nose system could be an efficient method to predict shelf-life and to evaluate quality in foods.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.68-84
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• 2020

This study analyzed the relationship between spatial characteristics and heat waves in the distribution area of the elderly population in Changwon, Gyeongsangnam-do. For analysis, the Statistics Census data, the Ministry of Environment land cover, Landsat 8 surface temperature, and the Meteorological Agency's heat wave days data were used. The spatial characteristics of the distribution of the elderly population was classified into 5 types through K-mean cluster analysis considering the land use types. The characteristics of the elderly population by spatial type were higher in the urbanized type(cluster-3), but the proportion of the elderly population was higher in the agricultural and forest area types(cluster-1, cluster-2). In the characteristics of the surface temperature and the heat wave days, the surface temperature was the highest in the urban area, but heat wave days were the highest in the rural area. As a result of analyzing the heat wave characteristics according to the spatial type of the distribution area of elderly population, cluster-2 with the largest area in agricultural areas was highest at 15.95 days, and cluster-3 with a large area in urbanized types was the lowest at 9.41 days and 9.18 days. In other words, the elderly population living in rural areas is more exposed to heat waves than the elderly population living in urban areas, and the damage is expected to increase. The results of this study could be used as basic data to prepare various policy measures for effective management and prevention of vulnerable areas in summer.

• Educational Technology International
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• v.18 no.2
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• pp.193-213
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• 2017

This study aimed to explore online learning profiles of in-service teachers in South Korea, focusing on video lecture and discussion activities. A total of 269 teachers took an online professional development course for 14 days, using an online learning platform from which web log data were collected. The data showed the frequency of participation and the initial participation time, which was closely related to procrastinating behaviors. A cluster analysis revealed three online learning profiles of in-service teachers: procrastinating (n=42), passive interaction (n=136), and active learning (n=91) clusters. The active learning cluster showed high-level participation in both video lecture and discussion activities from the beginning of the online course, whereas the procrastinating cluster was seldom engaged in learning activities for the first half of the learning period. The passive interaction cluster was actively engaged in watching video lectures from the beginning of the online course but passively participated in discussion activities. As a result, the active learning cluster outperformed the passive interaction cluster in learning achievements. The findings were discussed in regard to how to improve online learning environments through considering online learning profiles of in-service teachers.