• International Journal of Contents
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• v.17 no.4
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• pp.79-90
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• 2021

With the deepening of population aging, pension has become an urgent problem in most countries. Community smart pension can effectively resolve the problem of traditional pension, as well as meet the personalized and multi-level needs of the elderly. To predict the pension intention of the elderly in the community more accurately, this paper uses the decision tree classification method to classify the pension data. After missing value processing, normalization, discretization and data specification, the discretized sample data set is obtained. Then, by comparing the information gain and information gain rate of sample data features, the feature ranking is determined, and the C4.5 decision tree model is established. The model performs well in accuracy, precision, recall, AUC and other indicators under the condition of 10-fold cross-validation, and the precision was 89.5%, which can provide the certain basis for government decision-making.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1055-1067
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• 2019

In view of the deficiencies of existing weighted similarity indexes, a hierarchical clustering method initialize-expand-merge (IEM) is proposed based on the similarity of common neighbors for community discovery in weighted networks. Firstly, the similarity of the node pair is defined based on the attributes of their common neighbors. Secondly, the most closely related nodes are fast clustered according to their similarity to form initial communities and expand the communities. Finally, communities are merged through maximizing the modularity so as to optimize division results. Experiments are carried out on many weighted networks, which have verified the effectiveness of the proposed algorithm. And results show that IEM is superior to weighted common neighbor (CN), weighted Adamic-Adar (AA) and weighted resources allocation (RA) when using the weighted modularity as evaluation index. Moreover, the proposed algorithm can achieve more reasonable community division for weighted networks compared with cluster-recluster-merge-algorithm (CRMA) algorithm.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.163-177
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• 2021

Many methods of discovering social networking communities or clustering of features are based on the network structure or the content network. This paper proposes a community discovery method based on topic models using a time factor and an unsupervised clustering method. Online community discovery enables organizations and businesses to thoroughly understand the trend in users' interests in their products and services. In addition, an insight into customer experience on social networks is a tremendous competitive advantage in this era of ecommerce and Internet development. The objective of this work is to find clusters (communities) such that each cluster's nodes contain topics and individuals having similarities in the attribute space. In terms of social media analytics, the method seeks communities whose members have similar features. The method is experimented with and evaluated using a Vietnamese corpus of comments and messages collected on social networks and ecommerce sites in various sectors from 2016 to 2019. The experimental results demonstrate the effectiveness of the proposed method over other methods.

• Annual Conference of KIPS
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• 2011.11a
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• pp.1146-1149
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• 2011

N-screen 은 여러 단말을 통한 콘텐츠 소비형 서비스로써 이용자 환경과 요구사항에 반응하여 연속성을 가지고 이용자가 원하는 단말을 통해 제공될 수 있다. 자신이 가지고 있는 다양한 단말만 아니라 인증을 거친 다른 사용자가 가진 단말에도 N-screen 을 제공할 수 있다. 서로 다른 서비스 이용자 간 N-screen 을 제공하기 위한 플랫폼으로써 웹 플랫폼을 이용할 수 있다. 웹은 N-screen 을 제공하기 위해 가장 우선시 되는 요구사항인 플랫폼의 통합을 이끌어 낼 수 있으며 서비스 플랫폼과 협업을 통해 서비스 이용자의 요구사항을 만족시키고 동시에 Community 융합을 통해 전혀 새로운 서비스로 제공될 수 있다. 이에 본 논문에서는 웹 기반 N-screen 환경에서 Community 서비스 제공을 위한 서비스 제어기능 모델을 제안하고 그에 따른 서비스 시나리오를 설명한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.325-327
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• 2021

코로나19 전염병 예방을 위한 공공장소에서의 마스크 착용이 의무화되고 있다. 그러나 사람들이 다양한 이유로 마스크를 제대로 착용하지 않아 감염에 노출되는 위험이 발생하고 있다. 이러한 방역 문제를 해결하고 본 논문은 영상을 인식하여 마스크를 쓴 얼굴과 쓰지 않은 얼굴을 검출하는 방식을 제안한다. 제안 방법은 마스크 착용자와 비착용자 얼굴 영상을 딥러닝 기반의 YOLO 네트워크로 학습하여, 마스크 착용 유무를 판별한다. 동일 YOLO 네트워크에 대해 여러가지 조건으로 학습을 수행하고, 학습에 사용되지 않은 검증 데이터를 이용해 정확도가 가장 높은 네트워크의 가중치를 선택하였다. 실험결과, 마스크 착용자는 67.2%, 미착용자는 39.8%의 판별 정확도를 보였다. 미착용자에 대해 낮은 정확도를 보인 이유는 학습 데이터의 부족으로 판단되며, 이를 보완하기 위하여 더 많은 학습데이터를 제작하여 성능을 개선시키고자 한다.

• Journal of the Korean housing association
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• v.12 no.2
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• pp.55-63
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• 2001

The purpose of this study was to develop the community programs of multihousing in Korea through evaluating and analyzing the actual conditions of community in multihousing in U.S.A. This study was conducted by using a field survey and questionaire at the 2 multihousing complexes located in the City of Blacksburg, Virginia, U.S.A. The major findings were as follows: 1) There was a variety of community programs and facilities, such as a monthly newsletter which allowed information to be exchanged among all residents. The programs also provided news on events for the children, teenagers, college students, adults and seniors. These events were held at the club house or pond area. 2) The average degree of satisfaction of these programs and facilities was high. 3) Korea need to follow the example of the U.S.A by i) providing a monthly newsletter periodically to exchange information ii) offering a variety of community programs iii) providing programs regarding district bureau of public administration, kindergarten service, telecommunications office and holding service for package, registered mail, drycleaning, etc.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.64-66
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• 2005

한국과학기술정보원(KISTI) 바이오인포매틱스센터(CCBB)에서는 생명과학 관련 주제별 Open Archiving Community의 구성과 운영을 통한 연구자들 간의 정보교환을 유도하고, 더불어 논문뿐만 아니라 세미나, 연구노트 등의 최신의 연구 정보를 공유할 수 있도록 생명과학 Open Archiving Community 시스템을 구축하여 운영하려고 한다. 본 community에서 수집, 구축, 서비스할 점보의 종류는 아티클, 학위논문 연구보고서, 발표자료, 연구노트, 실험데이터, 전자자료 등이다. 그러므로, 전 세계적으로 많이 활용되고 있는 Dublin-core, Marc21, MODS를 비교 분석하여 MODS 메타데이터를 기준으로 아티클과 같은 문헌정보 뿐만 아니라 실험결과, 연구노트 등의 비문헌정보도 유연성 있게 적용할 수 있는 생명과학 관련 주제별 Open Archiving Community를 위한 메타데이터 스키마를 설계하였다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.183-192
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• 2005

Recently, community computing has been proposed for group formation and group decision-making. However, legacy community computing systems do not support group need identification for ad hoc group formation, which would be one of key features of ubiquitous decision support systems and services. Hence, this paper aims to provide a multi-agent based methodology to enable nomadic community computing which supports ad hoc need identification and group formation. Focusing on supporting group decision-making of relatively small sized multiple individual in a community, the methodology copes with the following three characteristics: (1) ad hoc group formation, (2) context-aware group need identification, and (3) using mobile devices working in- and out-doors. NAMA-US, an RFID-based prototype system, has been developed to show the feasibility of the idea proposed in this paper.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.11a
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• pp.145-145
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• 2007

• The Korean Journal of Ecology
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• v.22 no.5
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• pp.265-270
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• 1999

A syntaxonomical study about the vegetation of ruined salt field in Chonnam province was carried out and its soil properties were also determined. This study was accomplished by the methods of Mueller-Dombois and Ellenberg. This study was designed to clarify the syntaxonomical and synecological characteristics of the vegetation of ruined salt field in Chonnam province. The annual herbaceous halophyte communities of ruined salt field in Chonnam province were consisted of 5 communities: Salicornia herbacea community, Sueada japonica community, Sueada maritima community, Atriplex gmelini community, Spergularia marina community. And the perennial herbaceous halophyte communities of ruined salt field in Chonnam province were consisted of 3 communities: Aster tripolium community, Carex scabrifolia community, Phragmites communis community. The subsidiary knowledges of this study will make it possible to accumulate information on the distribution pattern of coastal salt marsh vegetation, and also will provide practical information for conservation of coastal ecosystems.