• Title/Summary/Keyword: trend analysis

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Analysis of Consulting Research Trends Using Topic Modeling (토픽 모델링을 활용한 컨설팅 연구동향 분석)

  • Kim, Min Kwan;Lee, Yong;Han, Chang Hee
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.4
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    • pp.46-54
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    • 2017
  • '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.

Concept of Trend Analysis of Hydrologic Extreme Variables and Nonstationary Frequency Analysis (극치수문자료의 경향성 분석 개념 및 비정상성 빈도해석)

  • Lee, Jeong-Ju;Kwon, Hyun-Han;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.4B
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    • pp.389-397
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    • 2010
  • This study introduced a Bayesian based frequency analysis in which the statistical trend analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both Gumbel distribution and trend analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions.

A Classification of Research Types and Trend Analysis of Research Methods in Korean for Academic Purposes (학문 목적 한국어교육의 연구 유형 분류와 연구 방법의 동향 분석)

  • Na, Wonju;Joo, Hyunha;Kim, Youngkyu
    • Journal of Korean language education
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    • v.28 no.1
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    • pp.79-111
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    • 2017
  • This study is a trend analysis study that discusses the current status and directions of research methods of KAP research. The existing trend ana lysis studies dealing with research methods have problems in that the classification criteria of the studies used are rough and different from each other, rendering comparison between studies being difficult, and do not comprehensively cover research methods of diversified KAP research. Therefore, this study examined the research methods of KAP research from a critical point of view and suggested a set of classification criteria and an analysis framework that can be used consistently in classification and analysis of future KAP research methods. Based on the theoretical background of second language studies and applied linguistics, this study revised and supplemented Brown (2015)'s research method types and selected 289 journals and theses/dissertations from 2012 to 2016 and classified them into a new analysis framework. The primary and secondary studies, which are the major categories, were 219 and 70, respectively, so it was confirmed that there were much more primary studies. The primary studies then were subdivided into 128 qualitative research studies, 142 survey research studies, and 23 quantitative research studies, pointing to the trend that survey and qualitative research methods were preferred. In the qualitative research approaches, there were 21 action research studies, which were used the most. In addition, such qualitative research approaches as case studies and narrative inquiries which were difficult to find in the past, have gradually increased, confirming that the diversification of research methods is becoming common. However, there were still many studies that did not explicitly put forward research questions and there were many studies that did not report reliability and effect sizes in quantitative research. Of the 23 quantitative studies, only 50% reported reliability, and only three reported effect sizes. In order to enable systematic reviews (meta-analysis) of quantitative research and expect quality improvement of research in future KAP research, reporting of quantitative research should be done more systematically. This study is meaningful in that a systematic and detailed analysis framework was proposed to classify various research methods in the future and that the problems and directions for improvement of the KAP research methods were discussed through the analysis of the research trend of the KAP studies for the last 5 years.

S&T Policy Trend Using Language Network Analysis: Focusing on Science and Technology Basic Plan

  • Kim, Yun Jong;Jeong, Dae-hyun;Oh, Hyunchul
    • Asian Journal of Innovation and Policy
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    • v.6 no.2
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    • pp.111-137
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    • 2017
  • This study analyzes a language network of Science and Technology Basic Plan, which is the basis for science and technology policy in Korea, for the next Science and Technology Basic Plan. Language network analysis was adopted for a quantitative approach measuring the trend of policies. Several techniques such as keyword analysis, language network map analysis, quantitative characteristics analysis and keyword-related major-word analysis have been performed. Results show that there are common policies emphasized by all Science and Technology Basic Plans in the past, and there are also specific policies emphasized in each period of the Science and Technology Basic Plan. These specific policies come from a 'change of times' when the Science and Technology Basic Plans were established, as well as the philosophy of the national government.

Comparison of Domestic and International Research Trend on Information Security (정보보안에 대한 국내외 연구 트렌드 비교)

  • Kim, Won-pil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.8
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    • pp.1811-1817
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    • 2015
  • This paper analyzes domestic research trend on information security, compares its results with international trends, and studies future directions we should have on national level. This research is a successor of the work for analysis of global research trend on information security. Therefore we select the same analysis method to compare domestic and international research trends exactly. To do this, we use domestic papers presented or published from 2001 to 2014, measure temporal relationship between technologies related to information security, analyze domestic research trends, and compare the results. Finally we will suggest our future direction through considering international future markets of technologies.

Comparative Analysis in Perception of Retro Fashion and New-tro Fashion Using Big Data (빅 데이터를 활용한 레트로 패션과 뉴트로 패션에 대한 인식 비교)

  • Kyung Ja Paek;Jeong-Mee Kim
    • Journal of the Korea Fashion and Costume Design Association
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    • v.25 no.1
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    • pp.83-96
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    • 2023
  • The purpose of this study is to compare and analyze the perception of retro fashion and new-tro fashion using big data. TEXTOM allowed the collection of big data on the words 'retro fashion' and 'new-tro fashion', which was refined afterwards. As for the data collection period, Jan. 1, 2019 to Nov. 30, 2022 was set. A top 50 list of words were extracted from this data based on appearance frequency. The extracted words were processed through Network centrality analysis and CONCOR analysis using Ucinet 6. The results are as follows. 1) In retro fashion, the appearance frequency of 'style' was the highest, followed by 'sensibility', 'color', 'trend', 'fashion', and 'brand'. These words came up with high TF-IDF values. Network centrality analysis discovered that 'color', 'style', 'trend', 'sensibility', and 'design' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; trends, styles, looks, and photos. 2) In new-tro fashion, the appearance frequency of 'retro' was the highest, followed by 'trend', 'generation', 'style', 'brand', and 'fashion'. These words also came up with high TF-IDF values. Network centrality analysis found that 'retro', 'trend', 'generation', and 'brand' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; style, brand, clothing, and trend. 3) New-tro fashion is included in retro fashion in that it reproduces the styles of the past. However, it is taken completely differently from generation to generation. Unlike the older generations, millennials actively accept newly created clothes and brands based on the past styles. They perceive it as a fashion that reveals their own unique tastes and tastes.

Trend Properties and a Ranking Method for Automatic Trend Analysis (자동 트렌드 탐지를 위한 속성의 정의 및 트렌드 순위 결정 방법)

  • Oh, Heung-Seon;Choi, Yoon-Jung;Shin, Wook-Hyun;Jeong, Yoon-Jae;Myaeng, Sung-Hyon
    • Journal of KIISE:Software and Applications
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    • v.36 no.3
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    • pp.236-243
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    • 2009
  • With advances in topic detection and tracking(TDT), automatic trend analysis from a collection of time-stamped documents, like patents, news papers, and blog pages, is a challenging research problem. Past research in this area has mainly focused on showing a trend line over time of a given concept by measuring the strength of trend-associated term frequency information. for detection of emerging trends, either a simple criterion such as frequency change was used, or an overall comparison was made against a training data. We note that in order to show most salient trends detected among many possibilities, it is critical to devise a ranking function. To this end, we define four properties(change, persistency, stability and volume) of trend lines drawn from frequency information, to quantify various aspects of trends, and propose a method by which trend lines can be ranked. The properties are examined individually and in combination in a series of experiments for their validity using the ranking algorithm. The results show that a judicious combination of the four properties is a better indicator for salient trends than any single criterion used in the past for ranking or detecting emerging trends.

Practical Text Mining for Trend Analysis: Ontology to visualization in Aerospace Technology

  • Kim, Yoosin;Ju, Yeonjin;Hong, SeongGwan;Jeong, Seung Ryul
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.8
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    • pp.4133-4145
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    • 2017
  • Advances in science and technology are driving us to the better life but also forcing us to make more investment at the same time. Therefore, the government has provided the investment to carry on the promising futuristic technology successfully. Indeed, a lot of resources from the government have supported into the science and technology R&D projects for several decades. However, the performance of the public investments remains unclear in many ways, so thus it is required that planning and evaluation about the new investment should be on data driven decision with fact based evidence. In this regard, the government wanted to know the trend and issue of the science and technology with evidences, and has accumulated an amount of database about the science and technology such as research papers, patents, project reports, and R&D information. Nowadays, the database is supporting to various activities such as planning policy, budget allocation, and investment evaluation for the science and technology but the information quality is not reached to the expectation because of limitations of text mining to drill out the information from the unstructured data like the reports and papers. To solve the problem, this study proposes a practical text mining methodology for the science and technology trend analysis, in case of aerospace technology, and conduct text mining methods such as ontology development, topic analysis, network analysis and their visualization.

Analysis of Drought Risk in the Upper River Basins based on Trend Analysis Results (갈수기 경향성 분석을 활용한 상류 유역의 가뭄위험 변동성 분석)

  • Jung, Il Won;Kim, Dong Yeong;Park, Jiyeon
    • Journal of The Korean Society of Agricultural Engineers
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    • v.61 no.1
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    • pp.21-29
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    • 2019
  • This study analyzed the variability of drought risk based on trend analysis of dry-seasonal dam inflow located in upper river basins. To this, we used areal averaged precipitation and dam inflow of three upper river dams such as Soyang dam, Chungju dam, and Andong dam. We employed Mann-Kendall trend analysis and change point detection method to identify the significant trends and changing point in time series. Our results showed that significant decreasing trends (95% confidence interval) in dry-seasonal runoff rates (= dam inflow/precipitation) in three-dam basins. We investigated potential causes of decreasing runoff rates trends using changes in potential evapotranspiration (PET) and precipitation indices. However, there were no clear relation among changes in runoff rates, PET, and precipitation indices. Runoff rate reduction in the three dams may increase the risk of dam operational management and long-term water resource planning. Therefore, it will be necessary to perform a multilateral analysis to better understand decreasing runoff rates.

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

  • Lee, Hyun Sang;Jo, Bo Geun;Oh, Se Hwan;Ha, Sung Ho
    • The Journal of Information Systems
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    • v.30 no.3
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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.