• Journal of Information Technology Applications and Management
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• 제19권4호
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• pp.1-18
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• 2012

This paper identifies technology trends of national research and development (national R&D) by exploiting Korean national R&D patents, ranging from 2007 to 2010. In this paper, co-word analysis (CWA), which is a method to identify the relationship among technology terms by using their co-occurrences, is incorporated into network analysis to visualize the relationships among technology keywords of national R&D patents and calculate network indexes concerning inter-relationship diversity and strength of technology keywords. As a result, this research found that inter-relationship among technology keywords in national R&D are getting increasingly strengthening in an overall sense. In addition, the keyword inter-relationship diversity-strength map proposed in this paper revealed some significant technological keywords of national R&D : core technology keywords including "sensor", "film" and "fuel" and emerging keywords including "biosensor" and "thermoelectric". Because the proposed approach helps identify interdisciplinary trends of technology keywords from a massive volume of national R&D patents in a visual and quantitative way, we expect that the approach can be incorporated as a preliminary into the R&D planning process to assist R&D policy makers to understand technology convergence of national R&D and develop relevant R&D policies.

• 한국IT서비스학회지
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• 제11권1호
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• pp.223-238
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• 2012

We have been provided with a plenty of information about IT through the conferences. However, it is hard to find enough information or the latest trends from conferences because there are too many conferences. In this situation, we analyzed the latest trends related to the field of IT by exploiting the Netminer which is one of the software for analysis of social networks and measuring the Cosine Similarity between conferences, based upon keywords which are included in the conferences. We analyzed keywords of 24 conferences related to the computer network part of the IEEE (Institute of Electrical and Electronics Engineers) in the case of foreign conferences. We also analyze keywords of the KIISE (Korean Institute of Information Scientists and Engineers) conferences in the case of domestic conferences, during 2009-2010. We identified the trends through the frequency of keywords, the change of top 10 keywords ranking and the similarity between conferences.

• 지능정보연구
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• 제17권1호
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• pp.127-138
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• 2011

대부분의 연구포털 사이트는 관심 분야의 논문을 획득하고자 하는 연구자를 대상으로 한 서비스를 주로 제공하고 있다. 하지만 이러한 서비스는 정확한 서지사항을 알고 있는 일부 사용자의 경우 손쉽게 이용할 수 있지만, 대부분의 이용자는 원하는 자료를 획득하기 위해 키워드 검색을 통한 반복적 시행착오를 겪게 된다. 특히 사용자가 익숙하지 않은 분야의 논문을 검색하는 경우에는, 찾고자 하는 논문의 적절한 키워드 자체를 알지 못하여 검색에 큰 어려움을 겪게 된다. 이러한 한계를 극복하기 위해 일부 연구포털 사이트에서는 온라인 쇼핑몰의 상품 추천에 주로 사용되어온 연관관계 분석 기반 키워드 추천 서비스를 채택하고 있다. 하지만 연관관계 분석에만 기반한 키워드 추천 방식은 두 키워드간의 단편적인 관계만을 알려줄 뿐, 해당 학술 분야와 관련된 전체 키워드 간의 복합적 연결 관계를 보여주기에는 한계가 있다. 따라서 본 논문에서는 연관관계 분석을 통해 빈발 출현 키워드 쌍을 추출하고 이를 근거로 전체 키워드 간 네트워크를 구축함으로써, 학술 분야별 중심 키워드 및 분야 간 융합을 위한 연계 키워드를 추천하기 위한 방법을 제시하고자 한다.

• Asia Marketing Journal
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• 제16권3호
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• pp.23-33
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• 2014

The selection of keywords for bidding is a critical component of paid search advertising. When the number of possible keywords is enormous, it becomes difficult to choose the best keywords for advertising and then subsequently to assess their effect. To this end, we propose an ultrahigh dimensional keyword selection approach that not only reduces the dimension for selections, but also generates the top listed keywords for profits. An empirical analysis using a unique panel dataset from a large online clothes retailer that advertises on the largest search engine in China (i.e., Baidu) is presented to illustrate the usefulness of our approach.

• 영재교육연구
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• 제26권2호
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• pp.347-363
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• 2016

본 연구는 사회네트워크분석(Social Network Analysis: SNA)방법을 활용하여 최근 6년간(2010~2015년)의 국내 및 해외 영재교육의 연구동향을 분석하는 데 목적을 두었다. 연구대상은 영재교육 관련 국내 KCI등재지인 '영재교육연구'(한국영재학회)와 '영재와 영재교육'(한국영재교육학회)에 게재된 논문 457편과 해외 SSCI학술지 'The Gifted Child Quarterly,' 'Journal for the Education of the Gifted,' 'High Ability Studies'에 게재된 논문 347편으로 선정하였으며, 각 논문의 영문 키워드를 추출한 후 SNA방법으로 키워드 네트워크와 연결중심성 분석을 실시하였다. 연구결과, 국내외 공통적으로 academically gifted, science gifted, gifted를 중심으로 achievement, identification, intelligence의 키워드 빈도가 가장 높게 나타났다. 따라서 영재를 대상으로 성취, 판별, 지능에 관련된 연구들이 가장 많이 이루어진 것으로 나타났다. 이외에도 cognitive, motivation, self-concept이 공통적인 관심 주제로 나타났다. 한편 국내에서는 creativity, gifted education, gifted education teacher를, 해외에서는 foreign countries, student attitudes를 키워드로 한 연구가 주를 이루었다. 국내 영재교육 연구에서는 해외와 달리 외국사례, 학생태도, 성별차이 관련 키워드 빈도가 거의 나타나지 않았다. 결론적으로 국내 영재교육 연구는 보다 다양한 관점에서 연구가 이루어져야 하는 것으로 해석되었다.

• Journal of applied mathematics & informatics
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• 제10권1_2호
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• pp.333-351
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• 2002

This paper introduces a search method based on conceptual graph. A hyperlink information is essential to construct conceptual graph in web. The information is very useful as it provides summary and further linkage to construct conceptual graph that has been provided by human. It also has a property which shows review, relation, hierarchy, generality, and visibility. Using this property, we extracted the keywords of web documents and made up of the conceptual graph among the keywords sampled from web pages. This paper extracts the keywords of web pages using anchor text one out of hyperlink information and makes hyperlink of web pages abstract as the link relation between keywords of each web page. 1 suggest this useful search method providing querying word extension or domain knowledge by conceptual graph of keywords. Domain knowledge was conceptualized knowledged as the conceptual graph. Then it is not listing web documents which is the defect of previous search system. And it gives the index of concept associating with querying word.

• 한국한의학연구원논문집
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• 제11권2호
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• pp.35-52
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• 2005

This study is to design a Semantic Navigation Retrieval System for Oriental Medicine Articles based on a XTM so that people can search and use them more effectively than before. Keywords extracted from articles are categorized 4 topics : herbs, prescription, disease, and action. Keywords analysis Ontology is modeled based on 4 topics and their relations, and then represented Topic maps. Next, Article analysis Ontology is consist of title, author, keywords, abstracts and organization Topics from metadata. Keywords and Article analysis Ontology were integrated through Keywords Topic. Korean Medical Article Retrieval System is optimistic in terms on search results supporting semantic navigation in the information service aspects and easier accessibility because all related information are semantically connected with each different DBs.

• 한국군사과학기술학회지
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• 제16권5호
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• pp.622-630
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• 2013

The purpose of this study is to investigate trends of characteristics and changes in the field of marine/naval/underwater military science and technology in Korea. This study analyzed the keywords that appeared in marine/naval/underwater section of the "Journal of the Korean Military Science and Technology" during the period, 1998~2012. One hundred and seven articles were analyzed by keywords in English. Four hundred and fifty four keywords in English were analyzed by appearance frequency. Finally those results of source literatures and keywords were compared with each other and a better direction for the future of the field with further studies was suggested.

• Safety and Health at Work
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• 제12권2호
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• pp.272-276
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• 2021

This brief report aims to establish the keyword content of studies on occupational health and safety-the key framework of the world of work in the trade and health domain. Data were collected from the SCOPUS database, focusing on articles on occupational health and safety and related keywords, with an emphasis on abstracts and titles. Data were analyzed and summarized based on keywords included from the MeSH database. There were 24,499 manuscripts in the domain and 1,346 (5.40%) occupational health-related keywords, including those that overlapped. The most frequently referenced occupational health-related keyword was "occupational health" (452 articles), followed by "occupational safety" (141 articles). There were fewer keywords on occupational health in the trade and health literature. As the world of work has been prioritized because of the recent new normal of work life since the COVID-19 pandemic, examining the focus of occupational health priorities within the global perspective is crucial.

• Journal of information and communication convergence engineering
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• 제19권1호
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• pp.48-53
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• 2021

Herein, we propose a document analysis system that analyzes papers or reports transformed into XML(Extensible Markup Language) format. It reads the document specified by the user, extracts keywords from the document, and compares the frequency of keywords to extract the top-three keywords. It maintains the order of the paragraphs containing the keywords and removes duplicated paragraphs. The frequency of the top-three keywords in the extracted paragraphs is re-verified, and the paragraphs are partitioned into 10 sections. Subsequently, the importance of the relevant areas is calculated and compared. By notifying the user of areas with the highest frequency and areas with higher importance than the average frequency, the user can read only the main content without reading all the contents. In addition, the number of paragraphs extracted through the deep learning model and the number of paragraphs in a section of high importance are predicted.