• Title/Summary/Keyword: 의미 네트워크 분석

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A Study on Key Delivery Protocols for End-to-End Secure Communication (종단 간 암호화 통신을 위한 키 전달 프로토콜에 관한 연구)

  • Kim, Jung-Yoon;Hwang, In-Yong;Lee, Jong-Eon;Kim, Seok-Joong;Lee, You-Shin;Choi, Hyoung-Kee
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2009.01a
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    • pp.391-394
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    • 2009
  • All-IP는 통신에 관련된 모든 개체가 IP를 사용하는 네트워크를 의미한다. All-IP 네트워크에서는 보안을 위해 통신 내용에 대한 암호화가 반드시 이루어져야 하며, 신뢰할 수 있는 3자 (trusted third party)는 서비스 중재 및 부가 서비스 제공을 위해 통신에 사용된 암호화 키를 획득할 수 있어야 한다. 이는 통신 개체가 다른 개체에게 암호화 키를 전달하는 메커니즘이 필요하다는 것을 의미한다. 우리는 본 논문을 통해, 통신 개체가 다른 개체에게 키를 전달하는 기법을 37에로 분류하고 각 기법에 대해 상세히 설명한다. 또한, 우리는 새로운 키 전달 프로토콜을 제안하고 3가지 운용 모드를 제시한다. 우리가 제안하는 프로토콜용 사용자의 필요에 따라 보안 기능을 선택적으로 운용할 수 있다. 성능평가 및 분석 결과에 따르면, 보안 가능과 성능은 뚜렷한 트레이드오프(trade-off) 관계가 있음을 알 수 있고, 기본적인 기능만을 운용할 경우 추가적인 오버헤드가 거의 없음을 알 수 있다.

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Design and Implementation of SRS Data Model for IoT Environment (IoT 환경을 위한 SRS 데이터 모델의 설계 및 구현)

  • Lee, Sukhoon;Jeong, Dongwon;Jung, Hyunjun;Baik, Doo-Kwon
    • Annual Conference of KIPS
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    • 2015.10a
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    • pp.1235-1238
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    • 2015
  • 센서 레지스트리 시스템(Sensor Registry System, CRS)은 이기종 센서 네트워크 환경에서 센서 데이터의 일관성 있는 의미 해석을 위하여 센서 메타데이터를 등록하고 관리하는 시스템이다. 최근 사물인터넷(Internet of Things, IoT) 패러다임이 대두됨에 따라 센서 네트워크의 개념 및 이용 목적 등이 변화되고 있으며, SRS 역시 이를 반영하여 센서와 연관된 데이터 모델의 개선 및 확장이 요구된다. 따라서 이 논문은 IoT 환경에서 기존 SRS를 개선하기 위하여 Semantic Sensor Network Ontology(SSNO) 기반의 SRS 데이터 모델을 제안한다. 이를 위하여 IoT 환경에서 SRS의 목적 및 요구사항을 분석하고 SSNO의 개념들 중 필요 요소와 불필요 요소를 반영하여 제안 모델을 설계한다. 또한 생성된 SRS 데이터 모델을 이용하여 관계형 데이터베이스로 구축하고 SRS를 웹 어플리케이션으로 구현한다. 제안하는 SRS 데이터 모델은 기존 모델들에 비해 SSNO 온톨로지를 가장 적합하게 표현하므로 풍부한 의미 처리가 가능하다.

The Influence of the Founder's Social Competence and Social Capital on Access to Funding Sources (창업자의 사회적 역량과 사회적 자본이 투자유치 시도방식에 미치는 영향)

  • Park, Gyehyun;Kim, Dohyeon
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.16 no.1
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    • pp.21-35
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    • 2021
  • Based on social capital theory, this study investigated the influence of the start-up founder's social competence on the start-up's access to funding sources and performance through the mediating role of the type of social network. This study aimed to examine two types of social networks empirically (i.e., personal networks and business networks) as social capital in analyzing the effect of the founder's social competence and social capital on the method of accessing funding sources. A self-report questionnaire was administered to 252 South Korean start-up founders whose businesses are based in South Korea. Path analysis and mediation effect analysis were performed by structural equation modeling(SEM) using STATA 16.1. This study examined the full mediating effect of the founder's social competence on his/her personal and business networks, respectively, and how the effect leads to different methods to approach funding sources. This is the first study in South Korea to analyze empirically how social competence has contrasting effects on personal and business networks as well as how each type of network varies in its influence on the method founders use to attract investment. This study is also significant in that it proposed a new methodology by utilizing the position generator as the measure of personal and business networks to analyze social networks in detail. The analyses of 252 survey data collected over a period of six months will be a valuable resource that may provide researchers, founders, investors, and other stakeholders in the start-up ecosystem with meaningful implications.

A Comparative Analysis Study of IFLA School Library Guidelines Using Semantic Network Analysis (언어 네트워크 분석을 통한 IFLA의 학교도서관 가이드라인 비교·분석에 관한 연구)

  • Lee, Byeong-Kee
    • Journal of Korean Library and Information Science Society
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    • v.51 no.2
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    • pp.1-21
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    • 2020
  • The purpose of this study is to explore semantic characteristics of IFLA school library guidelines through network analysis. There are two versions, 2002 edition and 2015 revision of the guidelines. This study analyzed the 2002 edition and 2015 revision of the IFLA school library guidelines view point of semantic network, and compared characteristics of two versions. The keywords were to extracted from two texts, semantic network were composed based on co-occurrence relations with keywords. The centrality(degree centrality, closeness centrality, betweenness centrality) was analyzed from the network. In addition, this study conducted topic modeling analysis using LDA function of NetMiner4.0. The result of this study is following these. First, When comparing the centrality, the 'Program, Teaching, Reading, Inquiry, Literacy, Media' keyword was higher in the 2015 revision than in the 2002 edition. Second, 'Inquiry' in degree centrality and 'Achievement' in closeness centrality which were not included in the 2002 edition top-ranked keyword list, have new appeared in 2015 revision. third, As a result of the analysis of topic modeling, compared to the 2002 version, the importance of topics on programs and services, teaching and learning activities of librarian teacher, and media and information literacy is increasing in the 2015 revision.

Research trends of archival information services using language network analysis (언어 네트워크 분석을 활용한 기록정보서비스 연구동향 분석)

  • So-Yeon, Kim;Eun-Ju, Lee
    • Journal of Korean Society of Archives and Records Management
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    • v.22 no.4
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    • pp.87-107
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    • 2022
  • This study aims to examine the meaning and category of archival information services and analyze its research results. To this end, the research scope of the archival information service was set by reviewing the definition, types, and subjects. A total of 183 journal articles were gathered, and content analysis was conducted in two stages. In addition to the overall research trend analysis based on quantitative indicators, an expanded content analysis and language network analysis were attempted using Node Excel. This study revealed that the archival information service research began in earnest after 2006 and that the user-centered paradigm is gradually being applied. However, limitations confirmed that the subject of discussion, research methods, and journals were biased, and expanding the horizon of future discussion was suggested.

Forecasting Market trends of technologies using Bigdata (빅데이터를 이용한 기술 시장동향 예측)

  • Mi-Seon Choi;Yong-Hwack Cho;Jin-Hwa Kim
    • Journal of Industrial Convergence
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    • v.21 no.10
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    • pp.21-28
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    • 2023
  • As the need for the use of big data increases, various analysis activities using big data, including SNS data, are being carried out in individuals, companies, and countries. However, existing research on predicting technology market trends has been mainly conducted using expert-dependent or patent or literature research-based data, and objective technology prediction using big data is needed. Therefore, this study aims to present a model for predicting future technologies through decision tree analysis, visualization analysis, and percentage analysis with data from social network services (SNS). As a result of the study, percentage analysis was better able to predict positive techniques compared to other analysis results, and visualization analysis was better able to predict negative techniques compared to other analysis results. The decision tree analysis was also able to make meaningful predictions.

Discovering Association Rules using Item Clustering on Frequent Pattern Network (빈발 패턴 네트워크에서 아이템 클러스터링을 통한 연관규칙 발견)

  • Oh, Kyeong-Jin;Jung, Jin-Guk;Ha, In-Ay;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.14 no.1
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    • pp.1-17
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    • 2008
  • Data mining is defined as the process of discovering meaningful and useful pattern in large volumes of data. In particular, finding associations rules between items in a database of customer transactions has become an important thing. Some data structures and algorithms had been proposed for storing meaningful information compressed from an original database to find frequent itemsets since Apriori algorithm. Though existing method find all association rules, we must have a lot of process to analyze association rules because there are too many rules. In this paper, we propose a new data structure, called a Frequent Pattern Network (FPN), which represents items as vertices and 2-itemsets as edges of the network. In order to utilize FPN, We constitute FPN using item's frequency. And then we use a clustering method to group the vertices on the network into clusters so that the intracluster similarity is maximized and the intercluster similarity is minimized. We generate association rules based on clusters. Our experiments showed accuracy of clustering items on the network using confidence, correlation and edge weight similarity methods. And We generated association rules using clusters and compare traditional and our method. From the results, the confidence similarity had a strong influence than others on the frequent pattern network. And FPN had a flexibility to minimum support value.

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R & D Networks Structure and Spatial Characteristics of Consumer Electronic Industry in Qingdao, China: The Case Study of Qingdao Haier Group in China (중국 가전산업의 연구개발 네트워크 구조와 공간적 특징 - 청도 하이얼(海爾, Haier) 그룹 사례 연구 -)

  • Quan, Guang-Ri;Ryu, Ju-Hyun;Lee, Sung-Cheol
    • Journal of the Economic Geographical Society of Korea
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    • v.15 no.2
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    • pp.292-303
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    • 2012
  • The main purpose of this study is to analyze R&D networks and spatial implications in Qingdao consumer electronics industry agglomeration in China. The characteristics of R&D networks in Qindao consumer electronic industry are as follows. There is a cluster central around large enterprises led by the government and their subcontracting enterprises. However, the degree of collaborative networks in intra-firm, inter-firm, firm-research institutes(including university lab.) is relatively low. Therefore, Large enterprises in Qingdao has stimulated research collaborations with firms and research institutes located in other regions rather than within region. It is likely to show that R&D networks of consumer electronics industry has not been stimulated in Qingdao. Therefore, collaborative R&D networks among firms, research institutes and governments should be stimulated to build regional innovation systems central around consumer electronics industry in Qingdao.

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Algorithmic Generation of Self-Similar Network Traffic Based on SRA (SRA 알고리즘을 이용한 Self-Similar 네트워크 Traffic의 생성)

  • Jeong HaeDuck J.;Lee JongSuk R.
    • The KIPS Transactions:PartC
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    • v.12C no.2 s.98
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    • pp.281-288
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    • 2005
  • It is generally accepted that self-similar (or fractal) Processes may provide better models for teletraffic in modem computer networks than Poisson processes. f this is not taken into account, it can lead to inaccurate conclusions about performance of computer networks. Thus, an important requirement for conducting simulation studies of telecommunication networks is the ability to generate long synthetic stochastic self-similar sequences. A generator of pseudo-random self similar sequences, based on the SRA (successive random addition) method, is implemented and analysed in this paper. Properties of this generator were experimentally studied in the sense of its statistical accuracy and the time required to produce sequences of a given (long) length. This generator shows acceptable level of accuracy of the output data (in the sense of relative accuracy of the Hurst parameter) and is fast. The theoretical algorithmic complexity is O(n).

Rank-Size Distribution with Web Document Frequency of City Name : Case study with U.S incorporated places of 100,000 or more population (인터넷 문서빈도를 통해 본 도시순위규모에 관한 연구 -미국 10만 이상의 인구를 갖는 도시들을 사례로-)

  • Hong, Il-Young
    • Journal of the Korean association of regional geographers
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    • v.13 no.3
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    • pp.290-300
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    • 2007
  • In this study, web document frequency of city place name is analyzed and it is used as the dataset for rank-size analysis. The search keywords are compared in the context of spatial meaning and the different domain corpus is applied. The acquired search results are applied for the further analysis. Firstly, the rank-size analysis is applied to compare the result between population and document frequency. Secondly, in case of correlation analysis, the significant changes are revealed when the spatial criteria for search keywords are increased. In case of corpus, COM, NET, and ORG shows the higher coefficient values. Lastly, the cluster analysis is applied to classify the list of cities that shows the similarity and difference. These analyses have a significant role in representing the rank-size distribution of city names that are reflected on the web documents in the information society.

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