• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.719-728
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• 2016

In this paper, we analyzed IoT patent data using the social network analysis of keyword community network in patents related to Internet of Things technology. To identify the difference of IoT patent trends between Korea and USA, 100 Korea patents and 100 USA patents were collected, respectively. First, we first extracted important keywords from IoT patent abstracts using the TF-IDF weight and their correlation and then constructed the keyword network based on the selected keywords. Second, we constructed a keyword community network based on the keyword community and performed social network analysis. Our experimental results showed while Korea patents focus on the core technologies of IoT (such as security, semiconductors and image process areas), USA patents focus on the applications of IoT (such as the smart home, interactive media and telecommunications).

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.227-240
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• 2011

New concepts and ideas often result from extensive recombination of existing concepts or ideas. Both researchers and developers build on existing concepts and ideas in published papers or registered patents to develop new theories and technologies that in turn serve as a basis for further development. As the importance of patent increases, so does that of patent analysis. Patent analysis is largely divided into network-based and keyword-based analyses. The former lacks its ability to analyze information technology in details while the letter is unable to identify the relationship between such technologies. In order to overcome the limitations of network-based and keyword-based analyses, this study, which blends those two methods, suggests the keyword network based analysis methodology. In this study, we collected significant technology information in each patent that is related to Light Emitting Diode (LED) through text mining, built a keyword network, and then executed a community network analysis on the collected data. The results of analysis are as the following. First, the patent keyword network indicated very low density and exceptionally high clustering coefficient. Technically, density is obtained by dividing the number of ties in a network by the number of all possible ties. The value ranges between 0 and 1, with higher values indicating denser networks and lower values indicating sparser networks. In real-world networks, the density varies depending on the size of a network; increasing the size of a network generally leads to a decrease in the density. The clustering coefficient is a network-level measure that illustrates the tendency of nodes to cluster in densely interconnected modules. This measure is to show the small-world property in which a network can be highly clustered even though it has a small average distance between nodes in spite of the large number of nodes. Therefore, high density in patent keyword network means that nodes in the patent keyword network are connected sporadically, and high clustering coefficient shows that nodes in the network are closely connected one another. Second, the cumulative degree distribution of the patent keyword network, as any other knowledge network like citation network or collaboration network, followed a clear power-law distribution. A well-known mechanism of this pattern is the preferential attachment mechanism, whereby a node with more links is likely to attain further new links in the evolution of the corresponding network. Unlike general normal distributions, the power-law distribution does not have a representative scale. This means that one cannot pick a representative or an average because there is always a considerable probability of finding much larger values. Networks with power-law distributions are therefore often referred to as scale-free networks. The presence of heavy-tailed scale-free distribution represents the fundamental signature of an emergent collective behavior of the actors who contribute to forming the network. In our context, the more frequently a patent keyword is used, the more often it is selected by researchers and is associated with other keywords or concepts to constitute and convey new patents or technologies. The evidence of power-law distribution implies that the preferential attachment mechanism suggests the origin of heavy-tailed distributions in a wide range of growing patent keyword network. Third, we found that among keywords that flew into a particular field, the vast majority of keywords with new links join existing keywords in the associated community in forming the concept of a new patent. This finding resulted in the same outcomes for both the short-term period (4-year) and long-term period (10-year) analyses. Furthermore, using the keyword combination information that was derived from the methodology suggested by our study enables one to forecast which concepts combine to form a new patent dimension and refer to those concepts when developing a new patent.

• Journal of the Korean Society for information Management
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• v.33 no.1
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• pp.53-84
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• 2016

This study clarified the intellectual structure of international collaboration in psychiatry based on analyzing networks in order to vitalize for international collaboration in psychiatry in South Korea. The data set was collected from Web of Science citation database during the period from 2009 to 2013. SU="psychiatry" search formulary (means field of psychiatric medical research) was used through advanced retrieval function and a total of 18,590 articles were selected among international collaborations. A total of 85 different keywords were selected from the 18,590 articles, and the results of analysis were as follows. First, this study examined 8 sub-subject areas focusing on disorders, and found that major subject areas could be divided into a total of 8 sub-subject areas. Second, this study examined 6 keywords that have a strong impact, and extend subject areas by promoting intermediation between other keywords Third, this study examined sub-subject areas by using the Knowledge Classification Scheme of the National Research Foundation of Korea through community analysis, and found a total of 15 clusters and a total of 12 sub-subject areas.

• Journal of Internet of Things and Convergence
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• v.4 no.1
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• pp.23-29
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• 2018

The purpose of study was to analyze the trends of 2005 to 2018 revised 'convergence technology research' through text network analysis using NetMiner4.0 program. Data analysis was conducted by using keyword analysis, centrality analysis of 653 authors' keyword from 177 journals. The results of the study are as follows. First, Research on Converging Technology has been studied steadily over the past 13 years in Department of Industry Convergence. Second, the results of the search term frequency analysis show that the 'convergence technology', 'technology convergence', 'convergence', 'design', 'convergence education', 'STEAM', 'convergence research' were used as the main keywords of convergence technology research. Third, Community analysis results show that five communities have been classified five categories according to the characteristics of the search terms 'only IT', 'Cultural industry utilizing Convergence contents', 'Technology innovation and research analysis' And patent development'. Based on these results, we proposed the future directions of convergence technology research.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.531-534
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• 2010

웹 2.0의 적극적인 도입에 따라 소셜 네트워크 기반 커뮤니티 사이트에서는 관련된 콘텐츠를 적절하게 추천하는 것은 중요한 문제로 부각되고 있으며 이로 인해 사용자들의 동향 및 이슈 추출 기법이 중요하게 작용하고 있다. 이러기 위해서 지금까지의 연구에서는 콘텐츠에 포함된 키워드 매칭 방법을 이용하고 있으나 사용자들 간의 연결 관계와 키워드의 중요도를 고려하지 못하고 있다. 본 논문에서는 FOAF 기반의 소셜 네트워크와 del.icio.us에서 제공하는 소셜 북마크 데이터를 기초로 소셜네트워크 분석을 보이며 이를 통한 사용자들 사이에서 중요하게 부각되는 핫 이슈를 추출하는 방법을 제안한다. 본 논문에서 제안하는 핫 이슈 추출 방법을 활용하면 사용자들의 관심 분야 동향파악을 효율적으로 수행할 수 있으며 이를 통해 맞춤형 마케팅 및 콘텐츠 추천이 가능해 진다.

• Electronics and Telecommunications Trends
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• v.26 no.4
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• pp.22-30
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• 2011

본 동향은 최근 이슈가 되고 있는 스마트TV 개발동향 및 시장전망에 대하여 알아보고, 스마트TV 검색 서비스에 대하여 소개한다. 스마트TV 검색 서비스는 사용자가 입력한 키워드 검색문의 의미를 해석하여 사용자가 의도하는 콘텐츠를 정확하게 찾아주는 시맨틱 기반 검색 서비스와 동일한 콘텐츠를 시청하고 있는 커뮤니티를 검색하여 콘텐츠에 대한 의견과 정보를 공유하는 소셜 네트워크 기반검색 서비스로 나누어 살펴본다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.432-433
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• 2024

오늘날 중요한 키워드로 꼽히는 블록체인은 탈중앙화를 핵심으로 하는 기술이며, DApp은 블록체인 플랫폼 기반의 분산형 애플리케이션이다. 본 논문에서는 블록체인 기반의 코인 시스템이 구축된 대학생 커뮤니티 애플리케이션을 개발하고자 한다. 애플리케이션의 사용자들은 각 게시판에서 지식과 정보를 공유하고 코인을 획득할 수 있다. 코인 시스템은 블록체인 네트워크와 애플리케이션이 연결됨으로써 애플리케이션을 통해 스마트 컨트랙트를 발행하는 방식이다. 또한, 블록체인 기술을 통해 유효한 가치를 가진 글은 영구적으로 보관할 수 있으며 획득한 코인으로는 현실의 재화로 교환할 수 있다. 본 애플리케이션을 통해 대학생들이 더 넓은 소통 창구를 가질 수 있을 것으로 기대된다.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.193-207
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• 2008

The study investigates the co-authorship networks of MIS Quarterly as one of the leading journals in IS field and examines patterns of collaboration networks of the intellectuals. These issues are addressed through a systematic Social Network Analysis (SNA) of 242 articles published from 1996 to 2004 in MIS Quarterly. Results of co-authorship network analysis indicate that the whole incomplete network has a low degree of density. Thus, we analyzed three biggest sub-networks to find out who the key players of each sub-network are. Then, following the keyword classification scheme, relevant data from the articles were collected and coded to analyze three major co-authorship networks of MIS Quarterly community. Some implications are drawn from different research keywords of each sub-network.

• The Korean Journal of Archival Studies
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• no.43
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• pp.147-177
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• 2015

This study presents the research trends of Records and Archives Management in Korea by analyzing the articles of the Records and Archives Management in Korea. For the study, 479 articles from 5 academic journals published between 2004 and 2013 were analyzed. The study employed content analysis and network analysis. As a result, summary of the study is as follows: First, the most frequently used keywords in the area of Korean Archival Studies were 'Record and Archive Management' and 'Archivist'. However 'Electronic Records'. 'Archival Reference Service' and 'Appraisal' have been used the most frequently when these general words have been excluded. Second, most participating institutions in journals, during the given period of the study, were Myongji University, Hankuk University of Foreign Studies, Chung-Ang University, and Pusan National University. Especially, MyongJi University and Chung-Ang University are core institutions in the Korean Archival Studies community.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.339-340
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• 2022

연구개발 활동을 지원하는 웹서비스 ScienceON은 논문, 특허, 연구보고서, 정책동향 정보뿐만 아니라 연구에 필요한 다양한 기능과 인프라를 통합적으로 제공하고 있다. 하지만 개인 데스크톱에서 활용이 용이한 검색 중심의 웹서비스는 언제 어디서나 쉽게 학술정보를 활용하고자 하는 사용자 요구를 충족시키기 어려운 문제가 있다. 연구자가 모바일 환경에서 쉽게 학술정보를 이용할 수 있는 환경을 제공하기 위해 본 논문에서는 검색 중심이 아닌, 개인의 관심정보와 논문 저자 식별 기반의 논문 피딩(feeding) 프로세스를 제안한다. 관심 분야 및 키워드 기반의 최신논문과 인기논문을 실시간으로 제공하고, 공저자 네트워크 및 저자 식별정보를 활용하여 최적화된 추천 논문을 제공한다. 또한 논문 중심의 커뮤니티를 제공하여 연구 활동 및 논문에 관한 다양한 의견 교환 채널로도 활용될 수 있다.