항공산업 미래유망분야 선정을 위한 텍스트 마이닝 기반의 트렌드 분석

김현정(Hyun-jung Kim),조남옥(Nam-ok Jo),신경식(Kyung-shik Shin) 한국지능정보시스템학회 2015 지능정보연구 Vol.21 No.1

Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

지역 패션산업 활성화를 위한 빅데이터 활용 및 연구동향 분석

최수경 한국지역경제학회 2023 韓國地域經濟硏究 Vol.21 No.1

The purpose of this study is to help revitalize the local fashion industry by analyzing the use of big data and research trends in the fashion industry. The scope of the study was set to the representative cases and studies of big data used in the fashion industry and fashion-related industries, and the method of study was academic data, research reports, Internet newspaper articles or trend reports Data such as videos, periodicals, and interviews were collected and analyzed for research. In this regard, this study obtained the following conclusions as a result of analyzing the use of big data and research trends in the fashion industry. Big data analysis in the fashion industry tends to be used and studied mainly in trend analysis, consumer analysis, design development, and inventory management. In trend analysis, trend analysis through big data can be an important predictive data at a time when small-quantity production of various types is oriented and the reactive production system (QRS) is actively used. In consumer analysis, consumer analysis through big data is most necessary at a time when SNS and online use is increasing due to changes in lifestyle and online shopping of consumers after the pandemic, and it is considered suitable as data to understand consumers. In design development, the use of big data will bring about innovative changes in the way of identifying and communicating the design needs of the public in the information age. In inventory management, by using big data, accurate analysis and forecasting, production and planning, and inventory criteria will be able to respond quickly to meet the needs and needs of consumers. In addition, the last 5 years, 3 years, and 1 year were analyzed with word cloud to find out the usage and research trends in the fashion industry with keywords related to the fashion industry applied to the actual web. As a result, in all of the 5-year, 3-year, and 1-year analyses, fashion, industry, and Seoul had a high proportion, especially fashion. PET bottles were also prominent in the 3-year analysis and worldwide in the 1-year analysis. 본 연구는 패션산업에서의 빅데이터 활용 및 연구동향을 분석하여 지역 패션산업의 활성화에 도움이 되는 데 그 목적이 있다. 연구의 범위는 패션산업 및 패션관련산업에서 활용되고 있는 빅데이터의 대표적인 사례 및 연구를 범위로 설정하였고, 연구의 방법은 패션과 빅데이터에 관련된 학술자료, 연구보고서, 인터넷 신문기사나 동향보고서, 동영상 및 정기간행물, 인터뷰 등의 자료를 수집, 분석하여 연구하였다. 이에 패션산업에서의 빅데이터 활용 및 연구동향을 분석한 결과 다음과 같은 결론을 얻었다. 패션업계의 빅데이터 분석은 트렌드 분석, 소비자 분석, 디자인 개발, 재고관리를 주축으로 활용되고 연구되는 경향을 보이고 있다. 트렌드 분석에서는 다품종소량생산을 지향하고, 반응생산시스템(QRS)이 활발히 이용되는 현황을 비추어 볼 때 빅데이터를 통한 트렌드 분석이 중요한 예측 자료가 될 수 있을 것이다. 소비자 분석에서는 팬데믹 이후 소비자들의 라이프스타일 변화와 온라인 쇼핑 증가로 SNS와 온라인 사용이 증가하고 있는 시점에서 빅데이터를 통한 소비자 분석이 무엇보다 필요하고 소비자를 이해하는 자료로 적합할 것으로 본다. 디자인 개발에서는 빅데이터 활용을 통해 정보화 시대에 대중의 디자인 니즈를 파악하고 소통하는 방법에 혁신적인 변화를 가져올 것이며, 이를 디자인 개발에 반영한다면 소비자의 요구를 즉각 반영한 상품 기획 및 구매로 이어질 것이다. 재고관리에서는 빅데이터 활용으로 정확한 분석과 예측, 생산 및 기획, 재고의 기준이 소비자의 요구도와 필요에 맞춰서 발 빠르게 대응할 수 있을 것이다. 추가적으로 실제 웹상에 적용된 패션산업 관련 키워드로 패션산업에서의 활용 및 연구동향을 알아보기 위해 최근 5년간, 3년간, 1년간 구분하여 워드클라우드로 분석해 보았다. 그 결과 5년간, 3년간, 1년간 분석 모두 패션, 산업, 서울시가 비중이 높게 나타났으며, 특히 패션이 압도적으로 높게 나타났다. 그리고 3년간 분석에는 페트병이, 1년간 분석에서는 글로벌이 두드러지게 부상하는 양상을 보였다.

Google Trends의 키워드 빅데이터 분석을 활용한 글로벌 스타트업 트렌드 분석: 2017~2022

김재억,전병훈 아이씨티플랫폼학회 2023 JOURNAL OF PLATFORM TECHNOLOGY Vol.11 No.4

In order to identify the trends and insights of 'startups' in the global era, we conducted an in-depth trend analysis of the global startup ecosystem using Google Trends, a big data analysis platform. For the validity of the analysis, we verified the correlation between the keywords 'startup' and 'global' through BIGKinds. We also conducted a network analysis based on the data extracted using Google Trends to determine the frequency of searches for the keyword or term 'startup'. The results showed a strong positive linear relationship between the keywords, indicating a statistically significant correlation (correlation coefficient: +0.8906). When exploring global startup trends using Google Trends, we found a terribly similar linear pattern of increasing and decreasing interest in each country over time, as shown in Figure 4. In particular, startup interest was low in the range of 35 to 76 from mid-2020 due to the COVID-19 pandemic, but there was a noticeable upward trend in startup interest after March 2022. In addition, we found that the interest in startups in each country except South Korea is very similar, and the related topics are startup company, technology, investment, funding, and keyword search terms such as best startup, tech, business, invest, health, and fintech are highly correlated. 글로벌시대의 환경속에서 '스타트업'의 트렌드와 인사이트를 파악하기 위해 빅데이터 분석 플랫폼인 Google Trends를 활용하여 최근 글로벌 스타트업 생태계를 심층 트렌드 분석을 실시하였다. 분석의 타당성을 위해 BIGKinds를 통해 핵심 키워드 '스타트업'과 '글로벌'의 상관관계를 검증하였다. 또한 '스타트업' 키워드나 용어의 검색 빈도를 파악하기 위해 Google Trends를 이용하여 추출한 데이터를 기반으로 네트워크 분석을 수행하였다. 연구결과, 키워드 사이에 강한 양적 선형관계를 보여주어 통계적으로 유의미한 상관관계를 나타냈다(상관계수: +0.8906). Google Trends를 사용한 글로벌 스타트업 트렌드를 탐색한 결과 ‘그림4’와 같이 각 국가들의 시기별 관심도가 증가하거나 감소하는 매우 비슷한 선형적 형태를 나타났다. 특히 스타트업 관심도가 2020년 중반부터 코로나-19 팬데믹으로 인해 35~76 범위내에서 낮게 나타났지만, 2022년 3월 이후 스타트업 관심도가 눈에 띄게 상승하는 트렌드를 보였다. 또한, 한국을 제외한 각 국가별 Startups 관심도는 아주 비슷한 추세이고, 관련 주제는 startup company, technology, investment, funding, 키워드 검색어는 best startup, tech, business, invest, health, fintech 등이 공통적으로 나타나 매우 높은 상관관계가 있음을 확인하였다.

Nano Technology Trend Analysis Using Google Trend and Data Mining Method for Nano-Informatics

Minsoo Shin(신민수),Min-Gyu Park(박민규),Seong-Hun Bae(배성훈) 한국산업경영시스템학회 2017 한국산업경영시스템학회지 Vol.40 No.4

Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users’ needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30’s, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.

나노 인포매틱스 기반 구축을 위한 구글 트렌드와 데이터 마이닝 기법을 활용한 나노 기술 트렌드 분석

신민수,박민규,배성훈 한국산업경영시스템학회 2017 한국산업경영시스템학회지 Vol.40 No.4

Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users’ needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30’s, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.

의미연결망 분석을 이용한 웹툰의 연구 동향 분석

정위,최동혁 한국만화애니메이션학회 2020 만화애니메이션연구 Vol.- No.59

This study analyzed the research trends of webtoons through semantic network analysis. Webtoons have received a lot of public, practical and academic attention over the past 15 years. However, the research results have not been comprehensively compiled yet. In response, 271 related papers were selected for analysis in order to identify research trends in core research and detailed research areas in the webtoon field, and a total of 726 keywords were extracted from these papers and a semantic network analysis was conducted on 99 keywords. The semantic network analysis provides a summary of the overall research performance in network form, based on the interrelationships between the detailed concepts used in a particular research field, as well as deriving the areas of study among the detailed concepts. In this study, a detailed technique of semantic network analysis was performed: keyword frequency analysis, centrality analysis, and cohesive group analysis by CONCOR. Key research concepts of webtoon research can be derived through frequency analysis and centrality degree analysis and can capture sub-research areas of webtoons based on the structural equivalence of the terminology index. The concept of core research in the field of webtoon research was identified through frequency analysis and centrality degree analysis through semantic network analysis. Keywords for narrative, storytelling, business model, cartoon and media conversion showed high frequency, followed by narrative, storytelling, business model, cartoon, content, platform, media conversion and brand webtoon. Overall, keywords such as narratives, storytelling, business models, and cartoons appear more frequently and are more centrality degree so it was understood that they are the main concept of the webtoon research. After checking the detailed research areas of the webtoon research field, it was confirmed that there were seven detailed research areas. [Group 1] Commercial use of webtoons, [Group 2] participation of webtoon users, [Group 3] production of webtoons, [Group 4] webtoons and Internet culture, [Group 5] webtoons education, [Group 6] media OSMU, and [Group 7] webtoons copyright. Based on the above analysis results, this study presented suggestions on the trend of webtoon research and methodology, and suggested research tasks and directions that should be solved in future research. 웹툰은 지난 15년 동안 대중적으로, 실무적으로, 또 학술적으로 많은 관심을 받아 온 주제이다. 그런데 아직 그 연구 내용과 결과가 종합적으 로 정리된 바 없다. 이에 본 연구는 의미연결망 분석을 통해 웹툰 연구를 분석하여 웹툰 분야의 핵심연구 및 세부연구영역 등의 연구 동향을 포착 하였다. 의미연결망 분석의 세부 기법인 빈도분석과 연결 중심성 분석을 통해 웹툰 연구의 핵심 연구개념을 도출할 수 있다. 구조적 등위성 분석 을 통해서는 웹툰의 하위연구 영역을 포착할 수 있다. 본 연구에서는 웹툰 관련 논문 271편을 분석대상으로 선정했으며, 이들 논문에서 총 726개의 키워드를 추출하여 그중 99개의 키워드를 대 상으로 의미연결망 분석을 하였다. 의미연결망 분석의 세부 기법인 키워 드 빈도분석, 연결 중심성 분석 및 구조적 등위성 분석을 하였다. 서사, 스토리텔링, 비즈니스 모델, 만화, 매체전환의 키워드가 높은 출현빈도를 보였으며, 서사, 스토리텔링, 비즈니스 모델, 만화, 콘텐츠, 플랫폼, 매체 전환, 브랜드 웹툰의 순으로 연결 중심성이 높게 나타났다. 서사, 스토리 텔링, 비즈니스모델, 만화와 같은 키워드들이 출현빈도도 높고 연결 중심 성도 높은 편이어서 웹툰 연구에서 주목하는 중점 개념임을 파악하였다. 웹툰 연구 분야의 세부 연구영역을 확인한 결과 7개의 세부 연구영역이 있는 것으로 확인되었다. [그룹 1] 웹툰의 상업적 활용, [그룹2] 웹툰 사 용자 참여, [그룹3] 웹툰 연출, [그룹4] 웹툰과 인터넷문화, [그룹5] 웹 툰 교육, [그룹6] 매체전환, [그룹7] 웹툰 저작권으로 그룹의 특성을 제 시하였다. 이상의 연구결과를 바탕으로 본 연구는 웹툰 연구 동향 및 방 법론에 대한 시사점을 제시하였으며, 향후 연구에서 해결해야 할 연구 과 제와 방향을 제언하였다

키워드 네트워크 분석을 활용한 과학기술동향 분석

박주섭(Ju Seop Park),김나랑(Na Rang Kim),한은정(Eun Jung Han) 한국산업정보학회 2018 한국산업정보학회논문지 Vol.23 No.2

학계나 연구소에서는 연구동향이나 과학기술동향을 파악하고 예측하기 위해 전문가들의 판단에 의존하는 정성적인 방법을 주로 활용하여 왔다. 이 기법은 많은 시간과 비용이 드는 단점이 있기에 본 논문에서는 키워드 네트워크 분석을 활용하여 과학기술 동향을 예측하였다. 이를 위해 미 국 특허 중 AI(Artificial Intelligence) 특허 초록 13,618개를 대상으로 키워드 네트워크 분석을 활용하여 분석 1기(2002.1.1. ~ 2006.12.31.), 분석 2기(2007.1.1. ~ 2011.12.31.), 분석 3기(2012.1.1. ~ 2016.12.31.)로 구분하여 분석하였다. 빈도 분석 결과, 분석 1기에서 3기로 시간이 경과할수록 AI 응용 분야의 방법에 관련된 핵심어들이 부각되었다. 키워드 네트워크 분석에서도 시간이 경과함에 따라 응용 분야의 방법에 관련된 핵심어와 다른 핵심어 간의 연계성이 높아졌다. 또한 분석 전체 기간 중 상승 및 하락 추세를 보인 연계 핵심어를 분석하면 응용 분야의 방법과 관리에 대한 연계성은 강화되는 반면에 기초 분야의 연계성은 약화되었다. 키워드 연결 중심성 분석에서도 기간이 경과할수록 응용 분야에 대한 중심성 수치가 높았다. 키워드 매개 중심성 분석에서 분석 3기는 응용 분야의 방법론관련 핵심어가 가장 높은 매개 수치를 보였다. 이는 앞으로 응용 분야의 방법들이 AI 분야의 강력한 중개자 역할을 할 것으로 예상된다. 본 논문에서 제시한 기법은 지역혁신과 관련된 과제 발굴이나 사회문제 이슈의 시각화 등 지역혁신 분야에 활용되어 질 수 있을 것이다. Academia and research institutes mainly use qualitative methods that rely on expert judgments to understand and predict research trends and science and technology trends. Since such a technique has the disadvantage of requiring much time and money, in this study, science and technology trends were predicted using keyword network analysis. To that end, 13,618 AI (Artificial Intelligence) patent abstracts were analyzed using keyword network analysis in three separate lots based on the period of the submission of each abstract: analysis period 1(January 1, 2002 — December 31, 2006), analysis period 2 (January 1, 2007 — December 31, 2011), and analysis period 3 (January 1, 2012 — December 31, 2016). According to the results of frequency analyses, keywords related to methods in the field of AI application appeared more frequently as time passed from analysis period 1 to analysis period 3. In keyword network analyses, the connectivity between keywords related to methods in the field of AI application and other keywords increased over time. In addition, when the connected keywords that showed increasing or decreasing trends during the entire analysis period were analyzed, it could be seen that the connectivity to methods and management in the field of AI application was strengthened while the connectivity to the field of basic science and technology was weakened. According to analysis of keyword connection centrality, the centrality value of the field of AI application increased over time. According to analysis of keyword mediation centrality during analysis period 3, keywords related to methodologies in the field of AI application showed the highest mediation value. Therefore, it is expected that methods in the field of AI application will play the role of powerful intermediaries in AI hereafter. The technique presented in this paper can be employed in the excavation of tasks related to regional innovation or in fields such as social issue visualization.

특수교육 분야 언어 네트워크 분석 연구의 동향

성한나(Han Na Sung) 학습자중심교과교육학회 2022 학습자중심교과교육연구 Vol.22 No.22

목적 본 연구는 국내 특수교육 분야에서 언어 네트워크 분석 방법을 활용한 연구들의 동향을 분석하여 향후 특수교육 분야에서 언어 네트워크 분석 관련 연구의 방향을 모색해보고자 하였다. 방법 이를 위하여 2007년부터 2022년 6월까지 국내 특수교육 분야의 언어 네트워크 분석 활용 연구 28편을 분석하였다. 분석기준은 선행연구를 기반으로 ‘발행연도 및 게재 학술지, 연구 주제, 분석 도구, 시각화 분석법, 분석지표’로 설정하였다. 결과 연구 결과, ‘특수교육재활과학연구’, ‘지적장애연구’에서 가장 많은 수의 연구가 수행된 것으로 나타났으며 2015년을 시작으로 점차 연구 수가 증가하여 2019년, 2021년에 가장 많은 연구(7편)가 수행되었음을 알 수 있었다. 또한, 대부분의 연구는 연구동향 및 지식구조 분석을 주제로 수행되었으며 그에 따라 수집 텍스트는 학술지 게재 논문이 대다수를 차지한 것으로 나타났다. 네트워크 분석 도구는 ‘UCINET’이 가장 많이 활용되었으며, 네트워크 지도를 통해 결과를 시각화한 연구가 가장 많았다. 분석대상 28편의 논문 모두에서 중심성 척도를 분석지표로 활용하고 있었으며 클러스터링, 에고 네트워크 분석 등의 방법도 사용되고 있었다. 결론 이러한 결과는 향후 특수교육 분야에서 언어 네트워크 연구 수행의 방향을 제공하는 데 의의를 가지며 질적으로 보다 다양한 주제의 연구가 지속적으로 확대될 필요성과 연구목적 및 주제에 적합한 네트워크 분석 도구, 시각화 제시 방법, 분석지표를 활용하여 연구 결과를 풍부하게 제시할 필요성에 관해 제언하였다. Objectives This study tried to explore the direction of language network analysis-related research in the field of special education in the future by analyzing the trends of studies using language network analysis methods in the field of special education in Korea. Methods For this purpose, 28 studies using language network analysis in the domestic special education field were analyzed from 2007 to June 2022. Based on previous research, the analysis criteria were set as ‘year of publication and published journal, research topic, analysis tool, visualization analysis method, and analysis index’. Results As a result of the study, it was found that the largest number of studies were conducted in ‘Special Education Rehabilitation Science Research’ and ‘Intellectual Disability Research’. was found to have been carried out. In addition, most of the research was conducted on the subject of research trend and knowledge structure analysis, and it was found that the majority of collected texts were articles published in academic journals. As a network analysis tool, ‘UCINET’ was used the most, and the most studies that visualized the results through a network map were the most. In all 28 papers to be analyzed, the centrality scale was used as an analysis index, and methods such as clustering and ego network analysis were also used. Conclusions These results have significance in providing a direction for conducting language network research in the field of special education in the future, and the need for continuous expansion of qualitatively more diverse topics, as well as network analysis tools, visualization presentation methods, and analysis suitable for research purposes and topics. The necessity of presenting the research results abundantly using indicators was suggested.

Pan 증발량 추세분포 분석

임창수(Rim Chang-Soo) 대한토목학회 2010 대한토목학회논문집 B Vol.30 No.3B

본 연구에서는 pan 증발량 분포와 추세를 분석하였다. 이를 위하여 전국 56개 기후관측지점에서 1973년부터 1990년까지의 pan 증발량 자료를 수집하여 분석을 실시하였다. 분석을 위하여 계절적 영향을 고려하여 1월, 4월, 7월 그리고 10월의 월평균 일별과 연평균 일별 pan 증발량 추세를 분석하였다. 연구결과 연평균 일별 pan 증발량은 56개 연구지역 중에서 38개 연구지역에서 감소추세를 보이고 있고, 1월 평균 일별 pan 증발량의 경우 33개 연구지역에서 pan 증발량 감소추세를 보이고 있다. 4월의 경우 38개 지역에서 증가추세를 보이고, 7월의 경우 47개 지역에서 감소추세를 보여서, 전반적으로 감소추세를 보이고 있다. 10월의 경우 35개 지역에서 증가추세를 보여서 전반적으로 증가추세를 보이고 있다. 따라서 전반적으로 연별과 1월, 7월은 pan 증발량이 감소추세를 보이고, 4월과 10월은 증가추세를 보이고 있다. 또한 인근에 위치한 권역별로도 다른 추세를 보이는 것으로 나타나서 지리지형적 요인이 pan 증발량 추세에 영향을 미치는 것으로 판단된다. 11개 기후관측지점에서 1973년부터 200년까지의pan 증발량 자료와 기후요소자료를 수집하여 추세분석을 실시한 결과, 기온, 상대습도 그리고 풍속추세는 연별이나 월별 pan 증발량 추세와 서로 같거나 또는 상이한 경향을 보이나, 일사량 추세는 연 및 월별 모두에서 pan 증발량 추세와 동일한 경향을 보이고, 강수량 추세는 연 및 월별 모두에서 pan 증발량 추세와 상반된 경향을보였다. The spatial distribution of pan evaporation and pan evaporation trends have been studied. In this study, pan evaporation data from 1973 to 1990 for 56 climatological stations were analyzed. In addition to annual average daily pan evaporation, monthly average daily pan evaporation in April, July, October and January were analyzed, considering seasonal effect. The study results indicate that in case of annual average daily pan evaporation, 38 stations out of 56 stations show decreasing trend. In case of average daily pan evaporation in January, 33 stations show decreasing trend. in April, 38 stations show increasing trend. In July, 47 stations show decreasing trend. In October, 35 stations show increasing trend. Therefore, on the whole, pan evaporation tended to decrease in January, July, and annual basis. On the other hand, pan evaporation tended to increase in April and October. Furthermore, pan evaporation trend in each individual region shows also different trend even though the region is located nearby, indicating that there are geographical and topographical effects on pan evaporation trend. Pan evaporation data and climatic data from 1973 to 2006 for 11 climatological stations were used for trend analysis. Climatic variables such as temperature, relative humidity and wind speed show same or opposite trend direction compared with pan evaporation in annual or monthly basis. Annual and monthly solar radiation trends show the same direction compared with pan evaporation; however, annual and monthly precipitation trends show the opposite direction compared with pan evaporation.

Analysis of Consulting Research Trends Using Topic Modeling

Min Kwan Kim(김민관),Yong Lee(이 용),Chang Hee Han(한창희) 한국산업경영시스템학회 2017 한국산업경영시스템학회지 Vol.40 No.4

‘Consulting’, which is the main research topic of the knowledge service industry, is a field of study that is essential for the growth and development of companies and proliferation to specialized fields. However, it is difficult to grasp the current status of international research related to consulting, mainly on which topics are being studied, and what are the latest research topics. The purpose of this study is to analyze the research trends of academic research related to ‘consulting’ by applying quantitative analysis such as topic modeling and statistic analysis. In this study, we collected statistical data related to consulting in the Scopus DB of Elsevier, which is a representative academic database, and conducted a quantitative analysis on 15,888 documents. We scientifically analyzed the research trends related to consulting based on the bibliographic data of academic research published all over the world. Specifically, the trends of the number of articles published in the major countries including Korea, the author key word trend, and the research topic trend were compared by country and year. This study is significant in that it presents the result of quantitative analysis based on bibliographic data in the academic DB in order to scientifically analyze the trend of academic research related to consulting. Especially, it is meaningful that the traditional frequency-based quantitative bibliographic analysis method and the text mining (topic modeling) technique are used together and analyzed. The results of this study can be used as a tool to guide the direction of research in consulting field. It is expected that it will help to predict the promising field, changes and trends of consulting industry related research through the trend analysis.