• Title/Summary/Keyword: 사회연결망모형

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A social network monitoring procedure based on community statistics (커뮤니티 통계량에 기반한 사회 연결망 모니터링 절차)

  • Joo Weon Lee;Jaeheon Lee
    • The Korean Journal of Applied Statistics
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    • v.36 no.5
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    • pp.399-413
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    • 2023
  • Recently, monitoring and detecting anomalies in social networks have become an interesting research topic. In this study, we investigate the detection of abnormal changes in a network modeled by the DCSBM (degree corrected stochastic block model), which reflects the propensity of both individuals and communities. To this end, we propose three methods for anomaly detection in the DCSBM networks: One method for monitoring the entire network, and two methods for dividing and monitoring the network in consideration of communities. To compare these anomaly detection methods, we design and perform simulations. The simulation results show that the method for monitoring networks divided by communities has good performance.

A Study on Containerports Clustering Using Artificial Neural Network(Multilayer Perceptron and Radial Basis Function), Social Network, and Tabu Search Models with Empirical Verification of Clustering Using the Second Stage(Type IV) Cross-Efficiency Matrix Clustering Model (인공신경망모형(다층퍼셉트론, 방사형기저함수), 사회연결망모형, 타부서치모형을 이용한 컨테이너항만의 클러스터링 측정 및 2단계(Type IV) 교차효율성 메트릭스 군집모형을 이용한 실증적 검증에 관한 연구)

  • Park, Ro-Kyung
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.9 no.6
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    • pp.757-772
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    • 2019
  • The purpose of this paper is to measure the clustering change and analyze empirical results, and choose the clustering ports for Busan, Incheon, and Gwangyang ports by using Artificial Neural Network, Social Network, and Tabu Search models on 38 Asian container ports over the period 2007-2016. The models consider number of cranes, depth, birth length, and total area as inputs and container throughput as output. Followings are the main empirical results. First, the variables ranking order which affects the clustering according to artificial neural network are TEU, birth length, depth, total area, and number of cranes. Second, social network analysis shows the same clustering in the benevolent and aggressive models. Third, the efficiency of domestic ports are worsened after clustering using social network analysis and tabu search models. Forth, social network and tabu search models can increase the efficiency by 37% compared to that of the general CCR model. Fifth, according to the social network analysis and tabu search models, 3 Korean ports could be clustered with Asian ports like Busan Port(Kobe, Osaka, Port Klang, Tanjung Pelepas, and Manila), Incheon Port(Shahid Rajaee, and Gwangyang), and Gwangyang Port(Aqaba, Port Sulatan Qaboos, Dammam, Khor Fakkan, and Incheon). Korean seaport authority should introduce port improvement plans by using the methods used in this paper.

Self-starting monitoring procedure for the dynamic degree corrected stochastic block model (동적 DCSBM을 모니터링하는 자기출발 절차)

  • Lee, Joo Weon;Lee, Jaeheon
    • The Korean Journal of Applied Statistics
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    • v.34 no.1
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    • pp.25-38
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    • 2021
  • Recently the need for network surveillance to detect abnormal behavior within dynamic social networks has increased. We consider a dynamic version of the degree corrected stochastic block model (DCSBM) to simulate dynamic social networks and to monitor for a significant structural change in these networks. To apply a control charting procedure to network surveillance, in-control model parameters must be estimated from the Phase I data, that is from historical data. In network surveillance, however, there are many situations where sufficient relevant historical data are unavailable. In this paper we propose a self-starting Shewhart control charting procedure for detecting change in the dynamic networks. This procedure can be a very useful option when we have only a few initial samples for parameter estimation. Simulation results show that the proposed procedure has good in-control performance even when the number of initial samples is very small.

Analysis of English abstracts in Journal of the Korean Data & Information Science Society using topic models and social network analysis (토픽 모형 및 사회연결망 분석을 이용한 한국데이터정보과학회지 영문초록 분석)

  • Kim, Gyuha;Park, Cheolyong
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.1
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    • pp.151-159
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    • 2015
  • This article analyzes English abstracts of the articles published in Journal of the Korean Data & Information Science Society using text mining techniques. At first, term-document matrices are formed by various methods and then visualized by social network analysis. LDA (latent Dirichlet allocation) and CTM (correlated topic model) are also employed in order to extract topics from the abstracts. Performances of the topic models are compared via entropy for several numbers of topics and weighting methods to form term-document matrices.

Model development for distributed instantaneous response function to investigate the network nonlinearity (네트워크의 비선형적 반응을 고찰하기 위한 분포형 순간반응함수 모형 개발)

  • Jisoo Lee;Kyungrock Paik
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.214-214
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    • 2023
  • 네트워크로 구성된 시스템은 물질, 에너지, 신호 등의 입력(input)이 주어졌을 때, 경로 추적, 즉 라우팅(routing)을 통해 출력(output)으로 연결되고, 이를 반응함수로 나타낼 수 있다. 같은 입력값이라도 네트워크에 따른 연결 구조와 라우팅 과정에서 소요되는 시간차에 따라 출력값이 달라질 수 있다. 좋은 예로 강우에 따른 유출반응함수를 나타내는 자연 하천망을 들 수 있다. 이론적으로 순간의 입력이 주어졌을 때 (입력의 지속시간이 0), 출력은 순간반응함수로 표현된다. 자연 하천망에 대한 선행연구에서는 강우강도에 따라 순간반응함수가 변화한다는 비선형성이 알려졌다. 하지만, 비선형성을 가져오는 물리적 과정에 대해서는 많은 연구가 필요하다. 이 연구는 격자 형태로 주어진 임의의 네트워크에서 각 격자에 대해 순간반응함수를 구하는 분포형 모형을 제시한다. 입력자료와 라우팅 방법에 따른 연결 구조 및 순간반응함수의 변화를 격자 별로 확인하고, 이를 통해 시스템의 비선형성을 고려할 수 있는지 고찰하였다.

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Recommender Systems using SVD with Social Network Information (사회연결망정보를 고려하는 SVD 기반 추천시스템)

  • Kim, Min-Gun;Kim, Kyoung-jae
    • Journal of Intelligence and Information Systems
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    • v.22 no.4
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    • pp.1-18
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    • 2016
  • Collaborative Filtering (CF) predicts the focal user's preference for particular item based on user's preference rating data and recommends items for the similar users by using them. It is a popular technique for the personalization in e-commerce to reduce information overload. However, it has some limitations including sparsity and scalability problems. In this paper, we use a method to integrate social network information into collaborative filtering in order to mitigate the sparsity and scalability problems which are major limitations of typical collaborative filtering and reflect the user's qualitative and emotional information in recommendation process. In this paper, we use a novel recommendation algorithm which is integrated with collaborative filtering by using Social SVD++ algorithm which considers social network information in SVD++, an extension algorithm that can reflect implicit information in singular value decomposition (SVD). In particular, this study will evaluate the performance of the model by reflecting the real-world user's social network information in the recommendation process.

Characteristics of Korean Film Market by Using Social Network Analysis (사회 연결망 분석을 이용한 국내 영화 시장의 특성 연구)

  • Kim, Tae-Gu;Cho, Nam-Wook;Hong, Jung-Sik
    • The Journal of the Korea Contents Association
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    • v.14 no.6
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    • pp.93-107
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    • 2014
  • Recently Korean film industry has continuously experienced a rapid growth and expanded its influence to foreign countries. Accordingly, there have been numerous studies in various research areas to investigate the characteristics of the industry. In this study, we applied social network analysis based on the attributes such as genres, ratings, distributors, nationalities, sizes, and profitability to divide the movies into several clusters with respect to their similarity. Results suggested that the ratings and nationality rather than the genre are the major factors to divide the motion picture market into clusters and the profitability also varies much across the clusters. Furthermore, estimation of the diffusion model showed the positive relationship between the success of a movie and the word-of-mouth effect, while the relatively unsuccessful titles exhibited a monotonic decreasing diffusion pattern with the high initial demand and the early peak time.

A Study on Social Capital of Strategy Alignment to IT Govenance in Digital Libraries (디지털도서관의 IT 거버넌스를 위한 전략적 연계의 사회적 자본 분석 모형)

  • Lee, Jeong-Soo;Kim, Seong-Hee
    • Journal of the Korean Society for information Management
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    • v.26 no.3
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    • pp.295-316
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    • 2009
  • This research applied the concepts of IT architecture and IT governance for managing with an integrated computing environment and organized structure, which base a digital library's management and operation. It also aims to analyze the structural system between information technology of human resources and strategy alignment elements of business, which both constitute the core content. Social network analysis software was used to investigate the complicated relationship between IT and business-related strategy alignment elements. The following is the results of carrying out this research on the social network structure and features of strategy alignment elements for a digital library. First, analysis indexes for strategy alignment elements and social network of a digital library were developed. Second, an analysis model was designed based on the analysis index for social network as to strategy alignment elements. Analysis model was appraised by collecting social network datasets for such strategy alignment elements as Communications, Competency and Value, Governance, Partnership, Scope and Architecture, and Skills against the Business strategy, Information strategy, Business and Technology of a digital library. As for the content of analysis, social network structure and specific features were analyzed in relation to a digital library's (1) General social network, (2) Structure of strategy alignment elements, (3) Strategy fit and Functional integration.

Predicting Snow Damage and Suggesting Improvement Plans Using Deep Learning (딥러닝을 이용한 대설피해액 예측 및 개선방안 제안)

  • Lee, HyeongJoo;Chung, Gunhui
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.485-485
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    • 2021
  • 최근 세계적인 기상이변으로 자연재해의 발생빈도 증가는 물론 이로 인한 피해가 점차 다양화 및 대형화되어 가고 있는 추세이다. 재난으로 인한 피해는 발생지역 피해뿐만 아니라 국가 경제 전반에 큰 영향을 미치는 특징이 있다. 우리나라의 자연재해 중 대설은 다른 자연재해에 비해 발생빈도는 낮지만 광역적인 피해를 유발하며, 피해 면적에 비해 피해액 규모가 크다. 또한 현재에는 강원권이 가장 취약한 것으로 취약성 분석 결과에서 보여주지만, 미래에는 강원권, 충청권, 호남권을 연결하는 축으로 취약지역이 확대될 것으로 전망된다. 본 연구에서는 현재 사회 전반에서 다양하게 활용되고 있는 머신러닝 기법을 이용하여 우리나라 대설피해액을 예측하는 대설피해 예측모형을 개발하고자 하였다. 머신러닝 기법으로는 랜덤포레스트, 서포트 벡터 머신, 인공신경망 기법을 이용하였고, 모형에 사용한 변수는 기상관측자료, 사회·경제적 요소 등을 활용하여 모형을 개발하였다. 결과적으로 기존연구에서 다중회귀모형을 이용하여 개발된 예측모형과 본 연구에서 3개의 머신러닝 기법으로 개발된 예측모형의 예측력을 비교 분석하였고, 예측력이 가장 높은 모형을 제시하였다. 본 연구결과를 활용하여 모형의 개선 및 데이터 품질 개선이 이루어진다면 향후 대설피해에 대한 개략적인 대비가 가능할 것으로 기대된다.

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A Study on the Vulnerability Assessment Model for National Defense Intelligence System Using SNA (사회연결망분석 개념을 적용한 국방정보체계 취약점 분석·평가 모형 연구)

  • Jang, Youngcheon;Kang, Kyongran;Choi, Bongwan
    • Journal of the Korea Institute of Military Science and Technology
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    • v.20 no.3
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    • pp.421-430
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    • 2017
  • In this research, we propose a methodology for assessing security vulnerability of the national defense intelligence system, considering not only target elements but also the interconnection relationship of the whole system. Existing approaches decide the security vulnerability of the whole system by assessing only target elements. However, those approaches have an issue with potentially showing the same outcome for the systems that have identical target elements but the different types of interconnection relationships. We propose a more practical assessment method which takes the interconnection relationship of a whole system into consideration based on the concept of SNA(Social Network Analysis).