• Title/Summary/Keyword: 텍스트 연구

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Trend Analysis using Topic Modeling for Simulation Studies (토픽 모델링을 이용한 시뮬레이션 연구 동향 분석)

  • Na, Sang-Tae;Kim, Ja-Hee;Jung, Min-Ho;Ahn, Joo-Eon
    • Journal of the Korea Society for Simulation
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    • v.25 no.3
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    • pp.107-116
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    • 2016
  • The recent diversification in terms of the scope and techniques used for simulations has highlighted the importance of analyzing state of the art trends and applying these for educational and study purposes. While qualitative methods such as literature research or experts' assessments have previously been used, such methods are in fact likely to reflect the subjective viewpoint of experts, and to involve too much time and money for the results obtained. For the purpose of an objective analysis, a quantitative analysis that included the examination of topics found in domestic academic journal articles was conducted in the present study. In this regard, simulation was found to be most actively used domestically in the electrical and electronic fields. In addition, simulation was also found to be employed for the purpose of education and entertainment in the social sciences. The results of this study are expected to help to facilitate the prediction of the direction of the development of not only the Korea Society for Simulation, but also domestic simulation studies. This study also raises the possibility of applying text mining to trend analysis, and proves that it can be a useful method for deriving future key topics and helping experts' decisions regarding quantitative data.

Abbreviation Disambiguation using Topic Modeling (토픽모델링을 이용한 약어 중의성 해소)

  • Woon-Kyo Lee;Ja-Hee Kim;Junki Yang
    • Journal of the Korea Society for Simulation
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    • v.32 no.1
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    • pp.35-44
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    • 2023
  • In recent, there are many research cases that analyze trends or research trends with text analysis. When collecting documents by searching for keywords in abbreviations for data analysis, it is necessary to disambiguate abbreviations. In many studies, documents are classified by hand-work reading the data one by one to find the data necessary for the study. Most of the studies to disambiguate abbreviations are studies that clarify the meaning of words and use supervised learning. The previous method to disambiguate abbreviation is not suitable for classification studies of documents looking for research data from abbreviation search documents, and related studies are also insufficient. This paper proposes a method of semi-automatically classifying documents collected by abbreviations by going topic modeling with Non-Negative Matrix Factorization, an unsupervised learning method, in the data pre-processing step. To verify the proposed method, papers were collected from academic DB with the abbreviation 'MSA'. The proposed method found 316 papers related to Micro Services Architecture in 1,401 papers. The document classification accuracy of the proposed method was measured at 92.36%. It is expected that the proposed method can reduce the researcher's time and cost due to hand work.

Recent Domestic Research Trend Over Startups: Focusing on the Social Network Analysis of Research Variables (스타트업 관련 최근 국내 연구 동향: 연구 변수들에 대한 소셜 네트워크 분석을 중심으로)

  • Kil, ChangMin;Yang, DongWoo
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.2
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    • pp.81-97
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    • 2022
  • This paper's purpose is to get hold of the recent research trend by analyzing the variables uesd in startups related papers. The startups related papers in this paper are the papers which include 'startups' in the title of the registered papers from the year 2013 to the year 2020. This study's analysis methods are text-mining of all variables and text-network analysis of affected variables. Visualizing tool for network analysis is Gephi. The result of variables' analysis is as follows. First, independent variables consist mainly of variables about startups' internal factors and outside environment, but due to startups' features like early stage company's features, innovative features, most of variables are about enterprise internal competitiveness, marketing 4P strategy, entrepreneurship, coopreation method, transformational leadership, enterprise features, lean startup strategy, enterprise internal communication, value orientation, task conflict, relationship conflict, knowledge sharing, etc. Second, dependent variables are mainly about outcome, and are classified into financial performance and non-financial performance by overall concept. In other words, startups related papers have higher interest in non-financial performance, like management performance, team performance, SCM performance as well as financial performance like sales quantity owing to startups' immaturity in getting good financial performance. Through this study we can find out as follows. Although there are not many officially registered papers dealing with startups, those papers include various themes about stratups. For example, there are trendy themes like lean startups strategy, crowdfunding, influencer and accelerator, etc.

A Study of Natural Landscape Information Management based Web Service (웹서비스기반의 자연경관정보관리 방안에 관한 연구)

  • Choi, Byoung-Gil;Kim, Uk-Nam;Na, Young-Woo
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2010.04a
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    • pp.125-127
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    • 2010
  • 본 연구의 목적은 인천지역의 자연경관정보를 보존하고 시민들에게 제공하기 위한 웹서비스기반의 자연경관정보의 관리방안에 대하여 연구하는데 있다. 지금까지의 인천시 관광전자지도는 관광지도로써 영상정보나 텍스트정보 중심으로 제공되고 있으나 인천지역의 특성에 맞는 위치정보기반 서비스 등 실용적인 정보가 부족한 형편이어서 GIS등 위치정보를 기반으로 한 사용자 참여 중심의 3차원 자연경관정보 관리방안을 연구할 필요가 있다.

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Ubiquitous Healthcare Protocol Description from Physician-centered to Participants-centered (의사-중심으로부터 참여자-중심의 유비쿼터스 헬스케어 프로토콜 기술)

  • Hwang, Gyeong-Sun;Lee, Seon-A;Lee, Geon-Myeong;Kim, Won-Jae;Yun, Seok-Jung;Ha, Yun-Seok
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.153-156
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    • 2007
  • 임상 프로토콜은 의료 서비스의 질을 향상시키는데 매우 중요한 수단 중 하나이다. 하지만 대부분의 임상 프로토콜이 텍스트 기반으로 되어 있을 뿐만 아니라 텍스트 기반의 임상 프로토콜들이 실행 가능한 형태로 시스템화가 되었더라도 치료를 하는 전문의의 관점에서만 기술되어 왔다. 한편 최근의 임상 연구는 유비쿼터스 헬스케어 서비스를 이용한 환자 개인의 맞춤형 의료서비스에 관한 연구가 진행되고 있다. 이와 같은 유비쿼터스 헬스케어 환경에서는 환자가 병원에서 뿐만 아니라 시간과 장소의 제약을 받지 않고 휴대용 단말기나 진단기기를 이용하여 효과적으로 의료 서비스를 제공 받을 수 있기 때문에 전문의뿐만 아니라 환자와 시스템도 헬스케어에 참여를 하게 된다. 따라서 전문의 중심의 임상 프로토콜 기술로부터 참여자 중심의 임상 프로토콜 기술이 절실히 요구된다. 본 논문에서는 전문의, 환자, 그리고 시스템의 역할에 따라 프로토콜 상에서 수행되어야 할 태스크들과 참여자들의 상태정보를 태스크 튜플 형태로 표현하였다. 하지만 태스크 튜플 기반의 표현 방법은 임상 프로토콜올 직관적으로 이해하는 데는 한계 있어 이러한 단점을 보완한 패트리 넷 기반의 유비쿼터스 헬스케어 프로토콜 기술 방법을 제안한다.

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An Experimental Study on Selecting Association Terms Using Text Mining Techniques (텍스트 마이닝 기법을 이용한 연관용어 선정에 관한 실험적 연구)

  • Kim, Su-Yeon;Chung, Young-Mee
    • Journal of the Korean Society for information Management
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    • v.23 no.3 s.61
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    • pp.147-165
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    • 2006
  • In this study, experiments for selection of association terms were conducted in order to discover the optimum method in selecting additional terms that are related to an initial query term. Association term sets were generated by using support, confidence, and lift measures of the Apriori algorithm, and also by using the similarity measures such as GSS, Jaccard coefficient, cosine coefficient, and Sokal & Sneath 5, and mutual information. In performance evaluation of term selection methods, precision of association terms as well as the overlap ratio of association terms and relevant documents' indexing terms were used. It was found that Apriori algorithm and GSS achieved the highest level of performances.

Design of a Sentiment Analysis System to Prevent School Violence and Student's Suicide (학교폭력과 자살사고를 예방하기 위한 감성분석 시스템의 설계)

  • Kim, YoungTaek
    • The Journal of Korean Association of Computer Education
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    • v.17 no.6
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    • pp.115-122
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    • 2014
  • One of the problems with current youth generations is increasing rate of violence and suicide in their school lives, and this study aims at the design of a sentiment analysis system to prevent suicide by uising big data process. The main issues of the design are economical implementation, easy and fast processing for the users, so, the open source Hadoop system with MapReduce algorithm is used on the HDFS(Hadoop Distributed File System) for the experimentation. This study uses word count method to do the sentiment analysis with informal data on some sns communications concerning a kinds of violent words, in terms of text mining to avoid some expensive and complex statistical analysis methods.

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Efficient Inverted List Search Technique using Bitmap Filters (비트맵 필터를 이용한 효율적인 역 리스트 탐색 기법)

  • Kwon, In-Teak;Kim, Jong-Ik
    • The KIPS Transactions:PartD
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    • v.18D no.6
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    • pp.415-422
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    • 2011
  • Finding similar strings is an important operation because textual data can have errors, duplications, and inconsistencies by nature. Many algorithms have been developed for string approximate searches and most of them make use of inverted lists to find similar strings. These algorithms basically perform merge operations on inverted lists. In this paper, we develop a bitmap representation of an inverted list and propose an efficient search algorithm that can skip unnecessary inverted lists without searching using bitmap filters. Experimental results show that the proposed technique consistently improve the performance of the search.

Remote Control Interaction for Individual Environment of Smart TV (개별 사용자 환경을 위한 스마트TV 리모트컨트롤 인터랙션 방식 제안)

  • Shin, Yoo-Kyung;Choe, Jong-Hoon
    • The Journal of the Korea Contents Association
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    • v.11 no.11
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    • pp.70-78
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    • 2011
  • Today cases of using individual service on community TV are increasing with the advent of smart TV. The traditional way for using individual service like e-mail or SNS on TV is not simple and puts in too much time because it has to type so many text using remote control that is unsuitable for typing. In this paper, interaction using cube remote control is proposed in order to facilitate individual service on TV. It is simple interaction like shaking and tapping instead of a complex interaction method. In addition, it is believed that the proposed simple interaction using cube interaction might be one of great alternatives for using individual service on smart TV.

Ethical Fashion Research Trend Using Text Mining: Network Analysis of the Published Literature 2009-2019 (텍스트 마이닝을 활용한 윤리적 패션 연구동향: 2009-2019 연구 네트워크 분석)

  • Choi, Yeong-Hyeon;Lee, Kyu-Hye
    • Fashion & Textile Research Journal
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    • v.22 no.2
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    • pp.181-191
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    • 2020
  • The fashion industry has faced environmental, social, and ethical issues due to increased interest in ethical consumption. Numerous ethical studies have been conducted in the fashion industry. This study looked at the current state of research by year, academic journal, and detail in major related papers published in Scopus, KCI and KCI between 2009 and 2019. Ethical fashion studies began to appear in 2009 and were concentrated in certain academic journals and focused on fashion marketing and fashion design. Topics in ethical fashion were terms such as sustainable, eco-friendly, up-cycling, recycling, eco, zero-waist, and organic. In ethical fashion studies, environmental studies were conducted most often; in addition, the terms used along with ethical fashion tend to be frequently used for each particular major. Looking at key words used in research by period, the study showed that research was most diverse between 2016 and 2019. In particular, environmental and social issues of ethical fashion and convergence with animal protection, new distribution, science and technology sectors were newly added between 2016 and 2019. This study used text mining and network analysis to understand the overall trends of ethical fashion studies in Korea. In conclusion it is important to realize the relationship between the main words along with the current status analysis.