• 제목/요약/키워드: structural-topic-modeling

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

  • 이현실;한성국
    • 정보관리학회지
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    • 제22권3호
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    • pp.289-306
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    • 2005
  • FRBR 모델에서는 서지 요소와 관계를 중심으로 ER 모델링 방식을 제공하고 있지만, 단지 구조적 프레임워크로서 FRBR 모델을 효율적으로 구현할 수 있는 도구가 필요하다. 본 연구에서는 Topic Maps를 이용하여 FRBR 모델을 구현하는 방법을 제시한다. Topic Maps 기반의 FRBR 모델 구현의 유효성을 실증적으로 보이기 위하여, 명성황후라는 주제와 관련된 MARC 데이터를 추출하여 FRBR 모델을 설계하였고, Topic Maps를 이용하여 이를 구현하였다. 연구 결과, FRBR의 entity-relation과 Topic Maps의 topic-association이 개념적으로 동일하기 때문에 FRBR 모델 개발의 적합함을 알 수 있었다. FRBR 구조는 Topic Maps 패러다임과 그대로 일치하기 때문에 FRBR 모델은 Topic Maps로 구현함이 바람직하다.

Topic Analysis of Scholarly Communication Research

  • Ji, Hyun;Cha, Mikyeong
    • Journal of Information Science Theory and Practice
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    • 제9권2호
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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.

User Review Mining: An Approach for Software Requirements Evolution

  • Lee, Jee Young
    • International journal of advanced smart convergence
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    • 제9권4호
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    • pp.124-131
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    • 2020
  • As users of internet-based software applications increase, functional and non-functional problems for software applications are quickly exposed to user reviews. These user reviews are an important source of information for software improvement. User review mining has become an important topic of intelligent software engineering. This study proposes a user review mining method for software improvement. User review data collected by crawling on the app review page is analyzed to check user satisfaction. It analyzes the sentiment of positive and negative that users feel with a machine learning method. And it analyzes user requirement issues through topic analysis based on structural topic modeling. The user review mining process proposed in this study conducted a case study with the a non-face-to-face video conferencing app. Software improvement through user review mining contributes to the user lock-in effect and extending the life cycle of the software. The results of this study will contribute to providing insight on improvement not only for developers, but also for service operators and marketing.

구조적 토픽모델링을 활용한 무료형 대규모 다중이용자 온라인 롤플레잉 게임의 소액결제에 대한 이용자 리뷰 분석 (User Review Analysis of Microtransactions in Freemium Massively Multiplayer Online Role-Playing Games Using Structural Topic Modeling)

  • 이철;정재은
    • Human Ecology Research
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    • 제61권3호
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    • pp.475-492
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    • 2023
  • This study investigated player responses to microtransactions in freemium Massively multiplayer online roleplaying games (MMORPG), specifically focusing on the game LostArk using English language review data. To this end, structural topic modeling was employed and the following six microtransaction-relevant topics were identified: microtransactions, developer issues, real money trade (RMT), random number generator (RNG) upgrade system, game content, and collectibles & adventure. The first four topics were classified as being "not recommended". However, the proportions of microtransaction-related topics were relatively lower than the other topics. Additionally, this study did not extract keywords related to unfairness and unethical issues in previous microtransaction research. The last two topics, game content, and collectibles & adventure were "recommended" topics, indicating positive functions of microtransactions such as enhancing the game experience by purchasing virtual items. Moreover, it was found that players who do not engage in microtransactions can still be satisfied through continuous game content updates. Additionally, an examination of the interaction effect between time and recommendation status revealed that while the frequency with which the six microtransaction-related topics were mentioned increased over time in the reviews, the ratio of recommendations to non-recommendations varied differently. This study contributes to game-related research by revealing players' authentic opinions on microtransactions in freemium MMORPGs, thereby providing practical implications for game companies.

섬유소재 분야 특허 기술 동향 분석: DETM & STM 텍스트마이닝 방법론 활용 (Research of Patent Technology Trends in Textile Materials: Text Mining Methodology Using DETM & STM)

  • 이현상;조보근;오세환;하성호
    • 한국정보시스템학회지:정보시스템연구
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    • 제30권3호
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    • pp.201-216
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    • 2021
  • Purpose The purpose of this study is to analyze the trend of patent technology in textile materials using text mining methodology based on Dynamic Embedded Topic Model and Structural Topic Model. It is expected that this study will have positive impact on revitalizing and developing textile materials industry as finding out technology trends. Design/methodology/approach The data used in this study is 866 domestic patent text data in textile material from 1974 to 2020. In order to analyze technology trends from various aspect, Dynamic Embedded Topic Model and Structural Topic Model mechanism were used. The word embedding technique used in DETM is the GloVe technique. For Stable learning of topic modeling, amortized variational inference was performed based on the Recurrent Neural Network. Findings As a result of this analysis, it was found that 'manufacture' topics had the largest share among the six topics. Keyword trend analysis found the fact that natural and nanotechnology have recently been attracting attention. The metadata analysis results showed that manufacture technologies could have a high probability of patent registration in entire time series, but the analysis results in recent years showed that the trend of elasticity and safety technology is increasing.

Customer Service Evaluation based on Online Text Analytics: Sentiment Analysis and Structural Topic Modeling

  • 박경배;하성호
    • 한국정보시스템학회지:정보시스템연구
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    • 제26권4호
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    • pp.327-353
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    • 2017
  • Purpose Social media such as social network services, online forums, and customer reviews have produced a plethora amount of information online. Yet, the information deluge has created both opportunities and challenges at the same time. This research particularly focuses on the challenges in order to discover and track the service defects over time derived by mining publicly available online customer reviews. Design/methodology/approach Synthesizing the streams of research from text analytics, we apply two stages of methods of sentiment analysis and structural topic model incorporating meta-information buried in review texts into the topics. Findings As a result, our study reveals that the research framework effectively leverages textual information to detect, prioritize, and categorize service defects by considering the moving trend over time. Our approach also highlights several implications theoretically and practically of how methods in computational linguistics can offer enriched insights by leveraging the online medium.

토픽모델링을 활용한 물리학 독서감상문 텍스트의 교육과정 연계성 분석 (Curriculum Relevance Analysis of Physics Book Report Text Using Topic Modeling)

  • 임정훈
    • 한국도서관정보학회지
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    • 제53권2호
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    • pp.333-353
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    • 2022
  • 본 연구는 '물리학' 수업에서 교과독서 활동으로 작성된 독후감상문의 교육과정 연계성을 분석하는데 목적이 있다. 연구를 수행하기 위해 교과독서 활동으로 작성한 332편의 물리학 독서감상문을 수집하여 키워드와 키워드들의 연결 관계를 분석하고, STM(Structural Topic Modeling)을 적용하여 토픽을 추출하였다. 분석 결과, 물리학 독서감상문의 주요 키워드는 '생각', '내용', '설명', '이론', '사람', '이해' 등으로 나타났으며, 도출된 키워드의 영향력과 연결 관계를 살펴보기 위해 연결중심성, 매개중심성, 위세중심성을 제시하였다. 토픽모델링 분석 결과, 물리학 교육과정과 관련된 11개 토픽이 추출되었으며, 3과목(물리학I, 물리학II, 과학사), 6개 영역(힘과 운동, 현대물리, 파동, 열과 에너지, 서양과학사, 과학이란 무엇인가)에서 교육과정 연계성을 확인할 수 있었다. 본 연구의 결과는 추후 교과 특성을 반영한 교과독서를 보다 체계적으로 시행할 수 있는 근거자료로 활용할 수 있을 것이다.

수산해양계열 고등학생의 전공만족, 진로탐색 자기효능감 및 진로탐색행동의 구조적 관계 연구 (A Study on the Structural Equation Modeling of the Relationships among Major Satisfaction, Career Search Efficacy, and Career Exploration Behavior with Marine Science High School Students)

  • 허균
    • 수산해양교육연구
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    • 제25권6호
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    • pp.1306-1314
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    • 2013
  • The purpose of this study is to find the structural relationships among major satisfaction, career search efficacy, and career exploration behavior with marine science high school students. For investigating this topic, 524 students were surveyed from the marine science high schools. In order to find out the structural relationships among major satisfaction, career search efficacy, and career exploration behavior, structural equation modeling was used. Followings were the results of the research: (a) Major satisfaction effected significantly on the career search efficacy. (b) Career search efficacy effected significantly on the career exploration behavior. (C) There was not significant direct cause and effects from major satisfaction to career exploration behavior, but indirect effect was significant. Some recommendations were suggested for increasing career exploration behavior of marine science high school students.

유튜브에서 다루어지는 갈등은 무엇인가?: 갈등 관련 유튜브 콘텐츠에 대한 토픽모델링 (What are the Conflicts Covered on YouTube?: Topic Modeling of Conflict-related YouTube Contents)

  • 임연수
    • 한국인터넷방송통신학회논문지
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    • 제23권1호
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    • pp.23-28
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    • 2023
  • 이 연구는 갈등 관련 유튜브 콘텐츠를 중심으로 유튜브 공간의 특성을 규명하는 데 목적이 있다. 2012년부터 2022년까지 유튜브에 게재된 갈등 관련 콘텐츠를 수집하고 토픽모델링 분석을 통해 주요 내용과 특성을 파악했다. 분석 결과, 갈등 관련 유튜브 콘텐츠는 사회 구조적 갈등에 대한 뉴스 보도와 가족 내 갈등을 다룬 방송 프로그램 위주로 구성되어 있었다. 이러한 결과는 유튜브 공간이 갈등 관련 문제에 대한 공론장으로 활용될 수 있다는 기대보다는 기존 방송 콘텐츠의 수익 창출 수단으로 기능하리라는 우려를 하게 만든다. 앞으로 우리 사회가 유튜브를 어떻게 활용할지에 대한 깊이 있는 논의가 필요한 시점이다.

키워드 네트워크 분석과 토픽모델링을 활용한 정보활용교육 연구 동향 분석 (Analysis of Research Trends in Information Literacy Education Using Keyword Network Analysis and Topic Modeling)

  • 임정훈
    • 정보관리학회지
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    • 제39권4호
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    • pp.23-48
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    • 2022
  • 본 연구는 키워드 네트워크 분석과 토픽모델링을 활용하여 국내 정보활용교육 연구의 흐름을 살펴보고 향후 정보활용교육의 방향성을 모색하는데 목적이 있다. 이를 위하여 국내 문헌정보학 분야의 학술지에 게재된 정보활용교육과 관련된 논문 306편을 선정하고, 논문의 초록을 대상으로 전처리 과정을 거쳐 전체 키워드 출현 빈도, 시기별 키워드 출현 빈도, 키워드 동시출현 빈도분석을 수행하였다. 이어서 키워드 네트워크 분석을 통해 키워드의 연결중심성과 매개중심성, 위세중심성을 분석하였다. 또한 구조적 토픽모델링 분석을 활용하여 15개의 토픽(교육과정, 정보활용교육 효과, 정보활용교육 내용, 학교도서관 교육, 정보매체활용, 정보활용능력 평가 지표, 도서관 불안, 공공도서관 프로그램, 대학도서관 이용자교육, 건강정보 활용능력, 정보격차, 도서관활 용수업 개선, 연구 동향, 정보활용교육 모델, 교사 역할)을 도출하고, 토픽별로 비중의 변화를 확인하기 위해 연도별 토픽 추이를 분석하였다. 이러한 결과를 바탕으로 정보활용교육의 방향성과 후속 연구에 대한 제언을 제시하였다.