• Title/Summary/Keyword: Between Centrality

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Neighbor Cooperation Based In-Network Caching for Content-Centric Networking

  • Luo, Xi;An, Ying
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.5
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    • pp.2398-2415
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    • 2017
  • Content-Centric Networking (CCN) is a new Internet architecture with routing and caching centered on contents. Through its receiver-driven and connectionless communication model, CCN natively supports the seamless mobility of nodes and scalable content acquisition. In-network caching is one of the core technologies in CCN, and the research of efficient caching scheme becomes increasingly attractive. To address the problem of unbalanced cache load distribution in some existing caching strategies, this paper presents a neighbor cooperation based in-network caching scheme. In this scheme, the node with the highest betweenness centrality in the content delivery path is selected as the central caching node and the area of its ego network is selected as the caching area. When the caching node has no sufficient resource, part of its cached contents will be picked out and transferred to the appropriate neighbor by comprehensively considering the factors, such as available node cache, cache replacement rate and link stability between nodes. Simulation results show that our scheme can effectively enhance the utilization of cache resources and improve cache hit rate and average access cost.

Influence Maximization against Social Adversaries (소셜 네트워크 내 경쟁 집단에의 영향력 최대화 기법)

  • Jeong, Sihyun;Noh, Giseop;Oh, Hayoung;Kim, Chong-Kwon
    • KIISE Transactions on Computing Practices
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    • v.21 no.1
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    • pp.40-45
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    • 2015
  • Online social networks(OSN) are very popular nowadays. As OSNs grows, the commercial markets are expanding their social commerce by applying Influence Maximization. However, in reality, there exist more than two players(e.g., commercial companies or service providers) in this same market sector. To address the Influence Maximization problem between adversaries, we first introduced Influence Maximization against the social adversaries' problem. Then, we proposed an algorithm that could efficiently solve the problem efficiently by utilizing social network properties such as Betweenness Centrality, Clustering Coefficient, Local Bridge and Ties and Triadic Closure. Moreover, our algorithm performed orders of magnitudes better than the existing Greedy hill climbing algorithm.

A Study on Technology Forecasting based on Co-occurrence Network of Keyword in Multidisciplinary Journals (다학제 분야 학술지의 주제어 동시발생 네트워크를 활용한 기술예측 연구)

  • Kim, Hyunuk;Ahn, Sang-Jin;Jung, Woo-Sung
    • Journal of the Korean Operations Research and Management Science Society
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    • v.40 no.4
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    • pp.49-63
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    • 2015
  • Keyword indexed in multidisciplinary journals show trends about science and technology innovation. Nature and Science were selected as multidisciplinary journals for our analysis. In order to reduce the effect of plurality of keyword, stemming algorithm were implemented. After this process, we fitted growth curve of keyword (stem) following bass model, which is a well-known model in diffusion process. Bass model is useful for expressing growth pattern by assuming innovative and imitative activities in innovation spreading. In addition, we construct keyword co-occurrence network and calculate network measures such as centrality indices and local clustering coefficient. Based on network metrics and yearly frequency of keyword, time series analysis was conducted for obtaining statistical causality between these measures. For some cases, local clustering coefficient seems to Granger-cause yearly frequency of keyword. We expect that local clustering coefficient could be a supportive indicator of emerging science and technology.

A Study on the Evaluation of Fashion Design Based on Big Data Text Analysis -Focus on Semantic Network Analysis of Design Elements and Emotional Terms- (빅데이터 텍스트 분석을 기반으로 한 패션디자인 평가 연구 -디자인 속성과 감성 어휘의 의미연결망 분석을 중심으로-)

  • An, Hyosun;Park, Minjung
    • Journal of the Korean Society of Clothing and Textiles
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    • v.42 no.3
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    • pp.428-437
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    • 2018
  • This study derives evaluation terms by analyzing the semantic relationship between design elements and sentiment terms in regards to fashion design. As for research methods, a total of 38,225 texts from Daum and Naver Blogs from November 2015 to October 2016 were collected to analyze the parts, frequency, centrality and semantic networks of the terms. As a result, design elements were derived in the form of a noun while fashion image and user's emotional responses were derived in the form of adjectives. The study selected 15 noun terms and 52 adjective terms as evaluation terms for men's striped shirts. The results of semantic network analysis also showed that the main contents of the users of men's striped shirts were derived as characteristics of expression, daily wear, formation, and function. In addition, design elements such as pattern, color, coordination, style, and fit were classified with evaluation results such as wide, bright, trendy, casual, and slim.

Analyzing the Ecosystem of the Domestic Online Game Industry : Focusing on the Linkage between Developers and Publishers (국내 온라인 게임 산업 생태계 분석 : 개발사-퍼블리셔 관계를 중심으로)

  • Chun, Hoon;Lee, Hakyeon
    • Journal of Korean Institute of Industrial Engineers
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    • v.42 no.2
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    • pp.138-150
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    • 2016
  • This study aims to analyze the structure and characteristics of the domestic online game industry using network analysis. In particular, two-mode network analysis is employed to measure the network structure, centrality, and cluster for two types of online game platforms, online games and mobile games, from 1996 to 2014. We also conduct a dynamic analysis to capture the structural changes in the ecosystem by internal and external environmental changes before and after turning point for each online game platform. It is revealed that the online game econsystem has the higher number of clusters and higher concentration ratio than those of mobile game ecosystem. In dynamic analysis, both platforms exhibit similar trends over time with the increasing number of clusters, enlargement of largest cluster's size, and decreasing concentration ratio. This study is expected to provide fruitful implications for strategic decision making of online game companies and policy making for the online game industry.

Self-rated Health and Global Network Position: Results From the Older Adult Population of a Korean Rural Village

  • Youm, Yoosik;Sung, Kiho
    • Annals of Geriatric Medicine and Research
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    • v.20 no.3
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    • pp.149-159
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    • 2016
  • Background: Since the mid-20th century, the ways in which social networks and older adults' health are related have been widely studied. However, few studies investigate the relationship between self-rated health and position in a complete social network of one entire Korean rural village. This study highlights use of a complete network in health studies. Methods: Using the Korean Social Life and Health Project, the population-based data of adults aged 60 or older and their spouses in one myeon in Ganghwa island (Ganghwa-gun, Incheon, Korea), Incheon, Korea (with a 95% response rate), this study built a $1,012{\times}1,012$ complete social network matrix of the village. The data were collected from 2011 to 2012, and 731 older adults were analyzed. The ordered logistic models to predict self-rated health allowed us to examine social factors from socio-demographic to individual community activities, ego-centered network characteristics, and positions in a complete network. Results: From the network data, 5 network components were identified. Even after controlling for all other factors, if a respondent belonged to a segregated component, the probability that he or she reported good health dropped substantially. Additionally, high in-degree centrality was connected to greater self-rated health. Conclusion: This finding highlights the importance of social position not only from the respondents' point of view but also from the entire village's perspective. Even if a respondent maintained a large social network, when all of those social ties belonged to a segregated group in the village, the respondent's health suffered from this segregation.

Finding Naval Ship Maintenance Expertise Through Text Mining and SNA

  • Kim, Jin-Gwang;Yoon, Soung-woong;Lee, Sang-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.7
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    • pp.125-133
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    • 2019
  • Because military weapons systems for special purposes are small and complex, they are not easy to maintain. Therefore, it is very important to maintain combat strength through quick maintenance in the event of a breakdown. In particular, naval ships are complex weapon systems equipped with various equipment, so other equipment must be considered for maintenance in the event of equipment failure, so that skilled maintenance personnel have a great influence on rapid maintenance. Therefore, in this paper, we analyzed maintenance data of defense equipment maintenance information system through text mining and social network analysis(SNA), and tried to identify the naval ship maintenance expertise. The defense equipment maintenance information system is a system that manages military equipment efficiently. In this study, the data(2,538cases) of some naval ship maintenance teams were analyzed. In detail, we examined the contents of main maintenance and maintenance personnel through text mining(word cloud, word network). Next, social network analysis(collaboration analysis, centrality analysis) was used to confirm the collaboration relationship between maintenance personnel and maintenance expertise. Finally, we compare the results of text mining and social network analysis(SNA) to find out appropriate methods for finding and finding naval ship maintenance expertise.

A Social Network Analysis on the Common Initiative for the Electronic Government Law: Focusing on the Ruling Party and Seniority Effect

  • Lee, Hun-Hee;Han, Sang-Ik
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.6
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    • pp.125-133
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    • 2019
  • This study aimed to investigate the political system related to the Electronic Government Law by analyzing the process of the common initiative of the law. To achieve the goal, this study applied the method of social analysis and sugessted the proper role of the assembly for realizing the electronic government and its control. The data were gathered from the bill information service of the national assembly. Netminer 4.0 was used for refining and analyzing data. The results are as follows. First, by analyzing three centrality(degree, betweenness, and eigenvector) of assembly member, the network effect of the powered party and reelected members were revealed as strong in the network. Second, through the component analysis, 5 sub-network has shown in total. The sub-networks showed two distinctive difference between two big parties. By the difference, members in two parties showed different characteristics in constituting communities and the effect of the powered party revealed as strong and clear. Based on the result, this study demonstrated the necessity of social solidarity rather than solipsism in committing common initiative. And a chronological research is need to anlayze $18^{th}$ and $19^{th}$ assembly to verify the effect of the powered party in prospect study.

A Study on the Analysis of Museum Gamification Keywords Using Social Media Big Data

  • Jeon, Se-won;Choi, YounHee;Moon, Seok-Jae;Yoo, Kyung-Mi;Ryu, Gi-Hwan
    • International Journal of Internet, Broadcasting and Communication
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    • v.13 no.4
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    • pp.66-71
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    • 2021
  • The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

A Study on the Promotion of Yakseon Food Using Big Data

  • LEE, JINHO;KIM, AE SOOK;Hwang, Chi-Gon;Ryu, Gi Hwan
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.4
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    • pp.41-46
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    • 2022
  • The purpose of this study is to confirm and analyze the impact on consumers through big data keyword analysis on weak food. For data collection, web documents, blogs, news, cafes, intellectuals, academic information, and Google Web, news, and Facebook provided by Naver and Daum were used as analysis targets. The data analysis period was set from January 2018 to December 2021. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analyzed and visualized using the Netdraw function among UCINET6 programs. In addition, CONCOR analysis was conducted to derive clusters for similar keywords. As a result of analyzing yakseon food with keywords, a total of 35,985 cases of collected data were derived. Through this, it was confirmed that medicinal food affects consumers. Furthermore, if a business model is created and developed through yakseon food, it will be possible to lead the popularization of yakseon food.