• Title/Summary/Keyword: 주제 연관성 기반 분류

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Research Trends in Steel Composite Beam Structures (최근 강구조 합성보의 연구현황 분석)

  • Ryu, Jaeho;Lee, Ja Young;Ju, Young K.;Kim, Sang Dae
    • 한국방재학회:학술대회논문집
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    • 2011.02a
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    • pp.27-27
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    • 2011
  • 기존에 연구 및 개발된 합성보 시스템에 대한 기초자료를 제공하고 앞으로 새로이 진행될 합성 구조 연구에 대한 방향을 제시하고자 국내 외 200여 편의 논문 및 학술기사를 기반으로 합성보에 대한 연구 및 기술 현황분석을 실시하였다. 그 결과 합성보에 대한 국내연구는 주로 실험적 연구가 63%로 해석적 연구(22%)에 비해 3배가량 높은 비율을 차지하고 있었으며, 국외의 경우 해석적 연구가 58%로 가장 높은 비중을 차지해 국내 연구방법과는 대조적인 모습을 나타냈다. 이에 앞으로는 지금까지 실시한 실험적 연구 내용을 토대로 보다 효율적인 연구 성과를 얻기 위해 해석적 연구의 기틀을 마련하는 것이 필요해 보였다. 또한 합성보 연구의 주제별 분류에 있어서도 기본적인 휨내력 평가뿐만 아니라 최근 들어, 관심이 높아진 사용자의 실제적인 생활 및 안전과 연관 있는 바닥진동, 충격음, 그리고 내화성능 등에 대한 다양한 검토가 깊이 있게 이루어져야 할 것이다. 마지막으로 기존의 구조용 재료를 대체하면서 경제적이고, 친환경성 및 재활용 재사용성 등을 고려한 미래지향적 합성구조시스템에 대한 연구 개발이 필요할 것으로 판단된다.

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Development of Topic Trend Analysis Model for Industrial Intelligence using Public Data (텍스트마이닝을 활용한 공개데이터 기반 기업 및 산업 토픽추이분석 모델 제안)

  • Park, Sunyoung;Lee, Gene Moo;Kim, You-Eil;Seo, Jinny
    • Journal of Technology Innovation
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    • v.26 no.4
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    • pp.199-232
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    • 2018
  • There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.

Change Detection of land-surface Environment in Gongju Areas Using Spatial Relationships between Land-surface Change and Geo-spatial Information (지표변화와 지리공간정보의 연관성 분석을 통한 공주지역 지표환경 변화 분석)

  • Jang Dong-Ho
    • Journal of the Korean Geographical Society
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    • v.40 no.3 s.108
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    • pp.296-309
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    • 2005
  • In this study, we investigated the change of future land-surface and relationships of land-surface change with geo-spatial information, using a Bayesian prediction model based on a likelihood ratio function, for analysing the land-surface change of the Gongju area. We classified the land-surface satellite images, and then extracted the changing area using a way of post classification comparison. land-surface information related to the land-surface change is constructed in a GIS environment, and the map of land-surface change prediction is made using the likelihood ratio function. As the results of this study, the thematic maps which definitely influence land-surface change of rural or urban areas are elevation, water system, population density, roads, population moving, the number of establishments, land price, etc. Also, thematic maps which definitely influence the land-surface change of forests areas are elevation, slope, population density, population moving, land price, etc. As a result of land-surface change analysis, center proliferation of old and new downtown is composed near Gum-river, and the downtown area will spread around the local roads and interchange areas in the urban area. In case of agricultural areas, a small tributary of Gum-river or an area of local roads which are attached with adjacent areas showed the high probability of change. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the capability of forest damage is very high. As a result of validation using a prediction rate curve, a capability of prediction of urban area is $80\%$, agriculture area is $55\%$, forest area is $40\%$ in higher $10\%$ of possibility which the land-surface change would occur. This integration model is unsatisfactory to Predict the forest area in the study area and thus as a future work, it is necessary to apply new thematic maps or prediction models In conclusion, we can expect that this way can be one of the most essential land-surface change studies in a few years.

An Investigation on the Periodical Transition of News related to North Korea using Text Mining (텍스트마이닝을 활용한 북한 관련 뉴스의 기간별 변화과정 고찰)

  • Park, Chul-Soo
    • Journal of Intelligence and Information Systems
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    • v.25 no.3
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    • pp.63-88
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    • 2019
  • The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.