• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.861-868
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• 2021

With the development of technology for visualizing big-data, tasks such as intuitively analyzing a lot of data, detecting errors, and deriving meaning are actively progressing. In this paper, we describe the design and implementation of a 3D analysis that collects and stores the writing data in Chinese characters provided by the Korean Classical Database of the Korean Classics Translation Institute, stores and progress the data, and visualizes the writing information in a 3D network diagram. It solves the problem when a large amount of data is expressed in 2D, intuitive that analysis, error detection, meaningful data extraction such as characteristics, similarity, differences, etc. and user convenience can be provided. In this paper, we improved the problems of analyzing Chosun dynasty poetry in Chinese characters using 2D visualization conducted in previous studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1445-1450
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• 2020

Recently, a hologram-like system to provide a realistic experience has been serviced in performances, exhibitions, education. The constructing method for the hologram-like system can be configured in various forms such as a pyramid-typed, a semi-transparent large screen form. However, in various types of hologram-like systems, it is difficult to provide adjustment by changing and revising the content according to the configured hardware characteristics. In this paper, we propose a novel technique that can automatically visualize virtual contents running on heterogeneous hologram-like systems. To change the content to a given hardware configuration, we receive pre-built simple text-based configuration data, and correcting process was performed. According to the results of this paper, we found automatically and easily corrected visualization with the given configuration of the hologram-like system. Also, the problem of reducing the time by manual control in various types of heterogeneous hologram systems was solved.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.167-176
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• 2023

In this paper, we designed and implemented a graph assessment module that can evaluate graphs in an programming assessment system based on text and numbers. The assessment method of the graph assessment module is self-evaluation that outputs two graphs generated by codes submitted by learners and by answers, automatic-evaluation that converts each graph image into an array, and gives feedback if it is wrong. The data used to generate the graph can be inputted directly or used from external data, and the method of generatng graph that can be evaluated is MATLAB style in matplotlib, and the graph shape that can be evaluated is presented in mathematics and curriculum. Through expert review, it was confirmed that the content elements of the assessment module, the possibility of learning, and the validity of the learner's needs were met. The graph assessment module developed in this study has expanded the evaluation area of the programming automatic asssessment system and is expected to help students learn data visualization.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.47-62
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• 2016

An integrated database(DB) system was developed to manage the marine geological data and geophysical data acquired from around the Korean peninsula from 2009 to 2013. Geological data such as size analysis data, columnar section images, X-ray images, heavy metal data, and organic carbon data of sediment samples, were collected in the form of text files, excel files, PDF files and image files. Geophysical data such as seismic data, magnetic data, and gravity data were gathered in the form of SEG-Y binary files, image files and text files. We collected scientific data from research projects funded by the Ministry of Oceans and Fisheries, data produced by domestic marine organizations, and public data provided by foreign organizations. All the collected data were validated manually and stored in the archive DB according to data processing procedures. A geographic information system was developed to manage the spatial information and provide data effectively using the map interface. Geographic information system(GIS) software was used to import the position data from text files, manipulate spatial data, and produce shape files. A GIS DB was set up using the Oracle database system and ArcGIS spatial data engine. A client/server GIS application was developed to support data search, data provision, and visualization of scientific data. It provided complex search functions and on-the-fly visualization using ChartFX and specially developed programs. The system is currently being maintained and newly collected data is added to the DB system every year.

• Information Systems Review
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• v.21 no.2
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• pp.117-137
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• 2019

In the Big Data era, data science has become popular with the production of numerous data in various domains, and the power of data has become a competitive power. There is a growing interest in unstructured data, which accounts for more than 80% of the world's data. Along with the everyday use of social media, most of the unstructured data is in the form of text data and plays an important role in various areas such as marketing, finance, and distribution. However, text mining using social media is difficult to access and difficult to use compared to data mining using numerical data. Thus, this study aims to develop Korean Natural Language Application (KoALA) as an integrated application for easy and handy social media text mining without relying on programming language or high-level hardware or solution. KoALA is a specialized application for social media text mining. It is an integrated application that can analyze both Korean and English. KoALA handles the entire process from data collection to preprocessing, analysis and visualization. This paper describes the process of designing, implementing, and applying KoALA applications using the design science methodology. Lastly, we will discuss practical use of KoALA through a block-chain business case. Through this paper, we hope to popularize social media text mining and utilize it for practical and academic use in various domains.

• Culinary science and hospitality research
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• v.23 no.8
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• pp.195-205
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• 2017

The purpose of this study was to compare the Starbucks in South Korea with Starbucks in U.S.A through the semantic network analysis of big data by collecting online data with SCTM(Smart Crawling & Text Mining) program which was developed by big data research institute at Kyungsung University, a data collecting and processing program. The data collection period was from January 1st 2014 to December 7th 2017, and packaged Netdraw along with UCINET 6.0 were utilized for data analysis and visualization. After performing CONCOR(convergence of iterated correlation) analysis and centrality analysis, this study illustrated the current characteristics of Starbucks for Korea and U.S.A reflected by the social network and the differences between Korea and U.S.A. Since the Starbucks was greatly developed, especially in Korea. this study also was supposed to provide significant and social-network oriented suggestions for Starbucks USA, Starbucks Korea and also the whole coffee industry. Also this study revealed that big data analytics can generate new insights into variables that have been extensively studied in existing hospitality literature. In addition, implications for theory and practice as well as directions for future research are discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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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.

• The Journal of Information Systems
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• v.31 no.2
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• pp.19-43
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• 2022

Purpose Due to the COVID-19 pandemic, many companies are building virtual workplaces based on virtual reality technology. Through this study, we intend to identify the trend of convergence and convergence research between virtual reality technology and work space, and suggest future promising fields based on this. Design/methodology/approach For this purpose, 12,250 bibliographic data of research papers related to Virtual Reality (VR) and Workplace were collected from Scopus from 1982 to 2021. The bibliographic data of the collected papers were analyzed using Text Mining and Pathfinder Network, Parallel Neighbor Clustering, Nearest Neighbor Centrality, and Triangle Betweenness Centrality. Through this, the relationship between keywords by period was identified, and network analysis and visualization work were performed for virtual reality-based workplace research. Findings Through this study, it is expected that the main keyword knowledge structure flow of virtual reality-based workplace convergence research can be identified, and the relationship between keywords can be identified to provide a major measure for designing directions in subsequent studies.

• Human Ecology Research
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• v.60 no.1
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• pp.21-38
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• 2022

This study uses text mining compares and contrasts consumers' social media discourses on dietary related zero-waste movement before and after COVID-19. The results indicate that the amount of buzz on social networks for the zero- waste movement has been increasing after COVID-19. Additionally, the results of frequency analysis and topic modeling revealed that subjects associated with zero-waste movement were more diversified after COVID-19. Although the results of a sentiment analysis and word cloud visualization confirmed that consumers' positive responses toward the zero-waste have been increasing, they also revealed a need to educate and encourage those who are still not aware of the need for zero-waste. Finally, consumers mentioned only a small number of companies participating in zero-waste movement on SNS, indicating that the level of active involvement by such companies is much lower than that of consumers. Theoretical and educational implications as well as those for government policy-making are considered.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.129-136
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• 2018

This study analyzed technology application field and technology transfer type related to the 4th industrial revolution using frequency, visualization, and association analysis of text mining of Big Data. The analysis was conducted between the last three years (2015 - 2017) registered with the NTB of KIAT transfer technology database was utilized. As a result of analysis, First, First, transfer technologies called core technologies of the Fourth Industrial Revolution are a lot of about robots, 3D, autonomous driving, and wearables. Second, as the year go by, transfer technolgy registration such as IoT, Cloud, VR is increasing. Third, the results of the association analysis of technology transfer type are as follows. IoT and VR showed preference for technology trading and licensing, autonomous driving technology trading, wearable licensing, robots preferring technology cooperation, licensing, and technology trading.