• International Journal of Contents
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• 제10권1호
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• pp.29-35
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• 2014

This paper proposes an approach for visualizing research trends using theme maps and extra information. The proposed algorithm includes the following steps. First, text mining is used to construct a vector space of keywords. Second, correspondence analysis is employed to reduce high-dimensionality and to express relationships between documents and keywords. Third, kernel density estimation is applied in order to generate three-dimensional data that can show the concentration of the set of documents. Fourth, a cartographical concept is adapted for visualizing research trends. Finally, relative vitalization information is provided for more accurate research trend analysis. The algorithm of the proposed approach is tested using papers about Traditional Korean Medicine.

• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.214-224
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• 2017

本文运用文献计量分析的可视化软件 CiteSpace 对 CNKI 数据库平台上收录的我国高校工程管理人才培养研究相关文献进行分析, 了解我国高校工程管理人才培养研究现状以及研究的发展轨迹。 研究结果显示: 我国高校工程管理人才培养研究持续活跃, 文献数量呈稳步上升趋势, 载文期刊分布广泛, 研究者多, 但各研究机构之间合作少; 研究热点主要集中在应用型工程管理人才培养,实践教学改革和课程体系改革等方面。 为此, 我国高校工程管理人才培养相关研究可加强学术团体间的合作, 拓展研究对象的范围, 丰富研究视角, 并进一步探讨 "新工科" 发展下的工程管理人才培养。

• 한국정보통신학회논문지
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• 제25권11호
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• pp.1696-1707
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• 2021

최근 정보 기술의 성장에 따라 디지털, 데이터, 인공지능 리터러시와 같은 다양한 리터러시에 대한 연구가 이루어지고 있다. 본 논문에서는, 빅데이터 분석에서 필수적이고, 일상생활 모바일 앱에서도 다양하게 쓰이는 데이터 시각화에 초점을 두고 있으며, 데이터 시각화 활용 능력을 측정하는 데이터 시각화 리터러시 평가 체계에 대해서 다룬다. 2016년에 개발된 영문형 데이터 시각화 활용 능력을 측정하는 평가 체계(VLAT, Visualization Literacy Assessment Test)에 대해서 설명하고, 한국형에 맞춰 개발한 K-VLAT 평가 체계를 소개한다. K-VLAT은 국내 사용자의 맥락에 맞춰 12개의 시각화와 53개의 문항을 웹서비스를 통해 제공한다. 또한, 데이터 시각화 리터러시의 연구 방향을 이해하기 위해서, 영문형 VLAT을 참조한 79건의 논문을 분석하였다. 연구 목적을 4개의 대분야 및 11개의 소분야로 분류하였으며, 데이터 시각화 리터러시와 관련한 인지, 체계에 대한 확장, 교육과의 연계, 사용자 중심형 대시보드 개발 및 효과 평가 등에 활용되고 있다. 이에 따른 K-VLAT의 향후 활용 방안에 대해서 논의한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권8호
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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.

• 한국CDE학회논문집
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• 제18권5호
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• pp.309-320
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• 2013

Augmented reality (AR) is considered to be an excellent user interface to a 3D information space embedded within physical reality. For this reason, it has been applied to various applications such as design, medical service, interaction, and collaboration. However, there is no formal way of analyzing the research trend and evolution of augmented reality. This paper identifies the research trend and change in augmented reality (AR) via co-citation analysis. The co-citation analysis provides how the AR research has evolved, who are main contributors, and which papers suggest essential and influencing impact. To systematically analyze the cocitation, we have retrieved 1,145 papers from the Web of Science and applied a scientomertric analysis using CiteSpace. Based on the co-citation analysis of authors and documents, it is possible to analyze the evolution of augmented reality, key authors and papers, and breakthroughs. We have also compared the proposed approach with survey papers written by experts so that the result of the co-citation analysis can compromise the qualitative result done by experts, and thus it can provide a different view and insight for visualizing the research on augmented reality.

• 인터넷정보학회논문지
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• 제15권6호
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• pp.65-75
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• 2014

본 논문의 주안점은 다양한 매스 미디어에 나타난 이벤트(event) 정보를 자동으로 인식하고, 이를 시간 및 장소 축으로 시각화함으로써 특정 이벤트의 시간의 흐름에 따른 장소 이동의 추이를 분석하는 데에 있다. 특히 사용자가 직접 작성한 소셜 미디어에 기반하여 이벤트를 추출하고 그들 간의 연속성 분석을 통해 해당 이벤트의 변화 방향성과 사회적 영향을 가늠할 수 있다. 연속성 이벤트의 특성을 규명하기 위해 2년간의 뉴스 기사 및 트윗(tweet)을 수집하여 관련 도메인 선정을 위한 전수조사를 수행하였다. 수행 결과, '질병'과 '여가'도메인을 선정, 본 논문에서 제안한 시각화 방법을 적용한 사례 연구를 통해 시간 및 장소 관점에서의 시각화를 통한 추이 분석의 효용성과 제안된 방법의 유용성을 검증하였다. 특히 단순 사실기반의 연속성 시각과 결과와 사용자의 관심도가 반영된 소셜 미디어에 기반한 연속성 시각화 결과를 비교한 결과, 같은 시기의 이벤트들이라 하더라도 사회적으로 미치는 파장이 큰 장소 이동의 흐름을 파악할 수 있음을 보였다.

• 융합보안논문지
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• 제17권5호
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• pp.27-34
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• 2017

보안경보 이벤트를 이용한 네트워크 보안상황 시각화 기술은 보안 장비들에서 발생하는 대량의 보안경보 이벤트들을 효율적으로 시각화하여 관리자에게 네트워크 내의 보안상황과 정보를 직관적으로 전달하는 기술이다. 하지만, 기존 대부분의 시각화 방법들은 시간 흐름에 중첩하여 이벤트를 표시하거나 또는 빈도수를 활용한 상위 개체 분석이 대부분이기 때문에 공격의 추이, 발생한 시점, 공격의 연속성, 그리고 보고된 공격 정보들 간의 연관 관계를 살펴보기 어려웠다. 본 논문에서는 시간 흐름에 따라 이벤트들을 나선형으로 배치하고 발생 시간들과 공격 유형을 함께 표시함으로써, 전체 공격의 추이와 개별 공격들의 연속성 및 지속성을 직관적으로 살펴 볼 수 있다. 또한 전체 공격자와 피해자간의 연관관계를 하나의 화면을 통해 제공함으로써 전체 공격상황 뿐만 아니라 공격 유형과 공격 지점 등을 종합적으로 인지할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3221-3242
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• 2021

The purpose of the study is to examine the current study trend of 'QR code' and suggest a direction for the future study of big data analysis: (1) Background: study trend of 'QR code' and analysis of the text by subject field and year; (2) Methodology: data scraping and collection, EXCEL summary, and preprocess and big data analysis by R x 64 4.0.2 program package; (3) the findings: first, the trend showed a continuous increase in 'QR code' studies in general and the findings were applied in various fields. Second, the analysis of frequent keywords showed somewhat different results by subject field and year, but the overall results were similar. Third, the visualization of the frequent keywords also showed similar results as that of frequent keyword analysis; and (4) the conclusions: in general, 'QR code' studies are used in various fields, and the trend is likely to increase in the future as well. And the findings of this study are a reflection that 'QR code' is an aspect of our social and cultural phenomena, so that it is necessary to think that 'QR code' is a tool and an application of information. An expansion of the scope of the analysis is expected to show us more meaningful indications on 'QR code' study trends and development potential.

• 산업경영시스템학회지
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• 제40권4호
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• pp.237-245
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• 2017

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.

• 한국정보시스템학회지:정보시스템연구
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• 제31권3호
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• pp.67-87
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• 2022

Purpose This study quantified companies' views on the COVID-19 pandemic with sentiment analysis of U.S. public companies' disclosures. It aims to provide timely insights to shareholders, investors, and consumers by analyzing and visualizing sentiment changes over time as well as similarities and differences by industry. Design/methodology/approach From more than fifty thousand Form 10-K and Form 10-Q published between 2020 and 2021, we extracted over one million texts related to the COVID-19 pandemic. Using the FinBERT language model fine-tuned in the finance domain, we conducted sentiment analysis of the texts, and we quantified and classified the data into positive, negative, and neutral. In addition, we illustrated the analysis results using various visualization techniques for easy understanding of information. Findings The analysis results indicated that U.S. public companies' overall sentiment changed over time as the COVID-19 pandemic progressed. Positive sentiment gradually increased, and negative sentiment tended to decrease over time, but there was no trend in neutral sentiment. When comparing sentiment by industry, the pattern of changes in the amount of positive and negative sentiment and time-series changes were similar in all industries, but differences among industries were shown in neutral sentiment.