• Title/Summary/Keyword: Topic-Association

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A method of Multi-Layer Visualizations for XTM (XTM을 위한 다층적 시각화 방법)

  • 박영조;박호병;조용윤;유재우
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10b
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    • pp.529-531
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    • 2004
  • 웹 상에는 많은 자원들과 정보들이 존재한다. XML은 이러한 자원들과 정보들을 구조화하기 위해서 개발되었다. XTM(XML Topic Maps)은 XML의 형태로 자원들과 정보들에 의미를 부여할 수 있는 언어이다. XTM은 Topic과 Association을 이용해서 자원들과 정보들이 가진 의미를 표현한다 XTM상에서 나타나는 Topic과 Association은 매우 거대하고 다양하기 때문에 모든 Topic과 Association을 한꺼번에 표현하기 어렵다 또한, 사용자가 수백만개의 Topic과 Association에서 원하는 Topic과 Association을 찾기 어렵다. 따라서 이러한 문제점을 해결하기 위해서 다양한 시각화 방법이 연구되었다. 현재 Topic Maps을 표현할 때 트리, 그래프, 맵 등 하나의 구조를 이용해서 표현한다. 하지만 추상화정도에 따라 시각화 방법은 장ㆍ단점을 지닌다. 본 논문에서는 웹 상의 자원, 정보들과 의미 사이에 여러 계층이 존재하는 다층적 시각화를 제안한다. 각 계층은 독립적인 표현구조로 나타내어 추상화정도에 따라 최적화된 구조를 사용한다. 사용자는 자신이 원하는 Topic과 Association을 점진적 접근을 통해서 원하는 Topic과 Association을 검색할 수 있다. 또한 Topic이 Association의 member처럼 사용되는 경우, 시각적으로 Topic이 표현되면 Topic은 연결된 Association과 직접적인 연결을 갖는다.

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An Implementation of FRBR Model by Using Topic Maps (Topic Maps를 이용한 MARC데이터의 FRBR모델 구현에 관한 연구)

  • Lee, Hyun-Sil;Han, Sung-Kook
    • Journal of the Korean Society for information Management
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    • v.22 no.3 s.57
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    • pp.289-306
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    • 2005
  • As FRBR defines structural framework based on ER modeling for bibliographic data elements, an effective tool is required to implement FRBR model. In this paper, we present the implementation of FRBR model based on Topic Maps. To show the effectiveness of Topic Maps as the implantation language of FRBR, we implement FRBR model of MyongSungHwangHu by means of Topic Maps. We can ascertain that topic-association of Topic Maps conceptually harmonize with entity-relation of FRBR, which means that Topic Maps is suitable for the implementation of FRBR model.

Personalized Topic map Ranking Algorithm using the User Profile (사용자 프로파일을 이용한 개인화된 토픽맵 랭킹 알고리즘)

  • Park, Jung-Woo;Lee, Sang-Hoon
    • Journal of KIISE:Software and Applications
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    • v.35 no.8
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    • pp.522-528
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    • 2008
  • Topic map typically provide information to user through the selection of topics, that is using only topic, association, occurrence on the first topicmap which is made by domain expert without regard to individual interests or context, for the purpose of supplementation for the weakness which is providing personalized topic map information, personalization has been studied for supporting user preference through preseting of customize, filtering, scope, etc in topic map. Nevertheless, personalization in current topicmap is not enough to user so far. In this paper, we propose a design of PTRS(personalized topicmap ranking system) & algorithm, using both user profile(click through data) and basic element of topic map(topic, association) on knowledge layer in specific domain topicmap, therefore User has strong point that is improvement of personal facilities to user through representation of ranked topicmap information in consideration of user preference using PTRS.

Topic Continuity in 5-Year-Old Children During Verbal Interactions With Peers (또래와의 언어적 상호작용에 나타난 만 5세 유아의 주제 수행 기술)

  • Sung, Mi Young
    • Korean Journal of Child Studies
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    • v.23 no.6
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    • pp.1-14
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    • 2002
  • This study investigated topic continuity in 5-year-old children during verbal interactions with peers by socioeconomic status and type of task. Each of the 78 children in this study participated in topic continuity sessions consisting of 4 l0-minute play periods with a same-sex peer : 2 in familiar and 2 in unfamiliar situations. Sessions were videotaped and transcribed. Transcripts were analysed by a modified version of the Kertoy and Vetter (1995) topic coding system; categories included topic initiation, topic continuation(collaboration and incorporation), and off-topic. Results showed that children from middle-income families stayed on topic and collaborated more than children from low-income families. Children displayed more topic continuation, collaboration and incorporation in familiar than in unfamiliar situations.

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Meta Analysis of Trade Insurance Using Text Mining (텍스트 마이닝을 활용한 무역보험분야의 메타분석)

  • Hyun-Hee Park;Sung-Je Cho
    • Korea Trade Review
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    • v.45 no.6
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    • pp.157-179
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    • 2020
  • This study presented the results of meta-analysis through topic modeling among the papers published in the Journal of the International Trade Association for the purpose of presenting academic research trends in the field of trade insurance and future research directions. Among the total 2,010 papers included in the Journal of the Korea International Trade Association, the analyzed paper covers the subject of trade-related insurance. According to detailed topics, 33 marine insurance (42.31%), 16 export insurance (20.51%), 11 hull insurance (14.10%), and 18 others (23.08%), and 4 other products liability insurance. According to the empirical analysis results, Topic 1 was classified as marine insurance, airworthiness, notice obligation, and collateral, and Topic 2 was derived as a representative topic for loading insurance, emergency risk, and immunity as export insurance. And Topic 3 was classified as vessel, sinking and container in relation to ship insurance, and Topic 4 was analyzed as an important topic such as manufacture and British marine insurance. Through the analysis results, we selected the representative topic used for the trade insurance topic and looked at the status of major research. Trade insurance is an area that requires the development of more theoretical and practical research subjects as an optimal risk management means in international trade transactions. To this end, first, support from the Korea International Trade Association is needed to establish a continuous research subject sharing system for the development of research subjects in the field of trade insurance. Second, academic journal operation management must be continuously managed in which academic research papers can be submitted and published.

Brand Personality of Global Automakers through Text Mining

  • Kim, Sungkuk
    • Journal of Korea Trade
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    • v.25 no.2
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    • pp.22-45
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    • 2021
  • Purpose - This study aims to identify new attributes by analyzing reviews conducted by global automaker customers and to examine the influence of these attributes on satisfaction ratings in the U.S. automobile sales market. The present study used J.D. Power for customer responses, which is the largest online review site in the USA. Design/methodology - Automobile customer reviews are valid data available to analyze the brand personality of the automaker. This study collected 2,998 survey responses from automobile companies in the U.S. automobile sales market. Keyword analysis, topic modeling, and the multiple regression analysis were used to analyze the data. Findings - Using topic modeling, the author analyzed 2,998 responses of the U.S. automobile brands. As a result, Topic 1 (Competence), Topic 5 (Sincerity), and Topic 6 (Prestige) attributes had positive effects, and Topic 2 (Sophistication) had a negative effect on overall customer responses. Topic 4 (Conspicuousness) did not have any statistical effect on this research. Topic 1, Topic 5, and Topic 6 factors also show the importance of buying factors. This present study has contributed to identifying a new attribute, personality. These findings will help global automakers better understand the impacts of Topic 1, Topic 5, and Topic 6 on purchasing a car. Originality/value - Contrary to a traditional approach to brand analysis using questionnaire survey methods, this study analyzed customer reviews using text mining. This study is timely research since a big data analysis is employed in order to identify direct responses to customers in the future.

A Design of K-XMDR Search System Using Topic Maps

  • Jialei, Zhang;Hwang, Chi-Gon;Jung, Gye-Dong;Choi, Young-Keun
    • Journal of information and communication convergence engineering
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    • v.9 no.3
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    • pp.287-294
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    • 2011
  • This paper proposes a search system using the topic maps that it extends XMDR into Knowledge based XMDR for solving of the problems of the heterogeneity of distributed data on a network and integrate data by an efficient way. The proposed system combined Topic Maps and the extended metadata registry effectively. The Topic Maps represent related knowledge and reasoning relationship by associations of topic. And the extended metadata registry standards and manages the metadata of the local systems through registration and certification on the distributed environment. We also proposed a meta layer, include the meta topic and meta association to achieve semantic classification grouping of topics and to define relationship between Topic Maps and extended metadata registry.

Topic Analysis of Scholarly Communication Research

  • Ji, Hyun;Cha, Mikyeong
    • Journal of Information Science Theory and Practice
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    • v.9 no.2
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    • pp.47-65
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    • 2021
  • This study aims to identify specific topics, trends, and structural characteristics of scholarly communication research, based on 1,435 articles published from 1970 to 2018 in the Scopus database through Latent Dirichlet Allocation topic modeling, serial analysis, and network analysis. Topic modeling, time series analysis, and network analysis were used to analyze specific topics, trends, and structures, respectively. The results were summarized into three sets as follows. First, the specific topics of scholarly communication research were nineteen in number, including research resource management and research data, and their research proportion is even. Second, as a result of the time series analysis, there are three upward trending topics: Topic 6: Open Access Publishing, Topic 7: Green Open Access, Topic 19: Informal Communication, and two downward trending topics: Topic 11: Researcher Network and Topic 12: Electronic Journal. Third, the network analysis results indicated that high mean profile association topics were related to the institution, and topics with high triangle betweenness centrality, such as Topic 14: Research Resource Management, shared the citation context. Also, through cluster analysis using parallel nearest neighbor clustering, six clusters connected with different concepts were identified.

Investigating the Trends of Research for the Small Business Owners (소상공인 연구 동향 분석)

  • Bang, Mi-Hyun;Lee, Young-Min
    • The Journal of the Korea Contents Association
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    • v.22 no.7
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    • pp.73-80
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    • 2022
  • In this study, prior studies of 280 small business owners in Korea over the past two decades were comprehensively analyzed through keyword network and LDA topic modeling analysis, and overall views and trends in academia were examined. As core keywords, "sales" and "protection," which conflict with each other but are essential for stable and sustainable growth were selected, and 7 topics (Topic 1: start-up, topic 2: digital, topic 3: tax system, topic 4: capability, topic 5: coexistence, topic 6: regulation, and topic 7: funding) were drawn up. Based on the results of the analysis, the need to improve digital maturity for the continued growth and development of small business owners was raised, and the response at the pan-ministerial level and the stability of the performance of functions that can survive even after the new administration to solve the economic damage problems facing small business owners were suggested. In addition, attention to the long-term, speed, detail, and direction of government support in a new way, and a flexible approach to the negative way in which pre-allowance and post-regulation is given were suggested.

How the Journal of the Korean Association for Science Education(JKASE) Changed for the Past 44 Years?: Topic Modeling Analysis Using Latent Dirichlet Allocation (한국과학교육학회지는 44년간 어떤 주제로 어떻게 변화했는가? -잠재 디리클레 할당(LDA)을 활용한 토픽모델링 분석-)

  • Chang, Jina;Na, Jiyeon
    • Journal of The Korean Association For Science Education
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    • v.42 no.2
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    • pp.185-200
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    • 2022
  • The purpose of this study is to understand the trends and changes of the articles publishing the Journal of the Korean Association for Science Education(JKASE) in the past forty-four years. To this end, Latent Dirichlet Allocation(LDA) topic modeling analysis was performed on a total of 2,115 English abstracts of papers published in the JKASE from 1978 to 2021. As a result of LDA topic modeling analysis, a total of 23 topics were extracted, and each topic was presented with its related keywords and articles. Next, in order to examine how these topics have changed over time, we visualized the average weights of each topic for a 4-year cycle by using heatmaps. The topics that have risen or fallen were identified. The results of this study provide new insights into science education research in Korea in terms of revealing not only traditional research topics that have been consistently studied but also the topics that have changed in response to the development of educational philosophy or research methods, social or policy demands related to science education.