• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.89-90
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• 2021

본 논문에서는 Python과 Selenium 라이브러리 기반의 재난 문자 크롤링 및 데이터 시각화 애플리케이션을 설계하고 구현한다. 이 애플리케이션의 특징은 웹상에서 재난 문자 데이터를 크롤링(Crawling)하여 그 빈도수에 따라 시각화하는 것이다. 이 애플리케이션을 활용하여 국민재난안전포털에 접속하여 재난 문자 데이터를 크롤링하고, 그 데이터를 Word Cloud를 활용하여 지역별 재난 문자 빈도수를 시각화한다. 지역별 재난 문자 빈도수를 한눈에 보기 쉽게 시각화함으로써 재난문자를 잘 확인하지 않는 사람들에게 해당 지역의 재난 정보를 쉽게 전달하는 기능을 제공한다.

• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.4
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• pp.33-37
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• 2022

Purpose: This study aims to understand the trend and central concept of domestic researches on laughter therapy. For the analysis, this study used total 72 theses verified by inputting the keyword 'laughter therapy' from 2007 to 2021. Research design, data and methodology: This study performed the development and analysis of keyword co-occurrence network, analyzed the types of researches through topic modeling, and verified the visualized word cloud and sociogram. The keyword data that was cleaned through preprocessing, was analyzed in the method of centrality analysis and topic modeling through the 1-mode matrix conversion process by using the NetMiner (version 4.4) Program. Results: The keywords that most appeared for last 14 years were laughter therapy, depression, the elderly, and stress. The five topics analyzed in thesis data from 2007 to 2021 were therapy, cognitive behavior, quality of life, stress, and the elderly. Conclusions: This study understood the flow and trend of research topics of domestic laughter therapy for last 14 years, and there should be continuous researches on laughter therapy, which reflects the flow of time in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4204-4222
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• 2015

Cloud is the latest buzz word in the internet community among developers, consumers and security researchers. There have been many attacks on the cloud in the recent past where the services got interrupted and consumer privacy has been compromised. Denial of Service (DoS) attacks effect the service availability to the genuine user. Customers are paying to use the cloud, so enhancing the availability of services is a paramount task for the service provider. In the presence of DoS attacks, the availability is reduced drastically. Such attacks must be detected and prevented as early as possible and the power of computational approaches can be used to do so. In the literature, machine learning techniques have been used to detect the presence of attacks. In this paper, a novel approach is proposed, where intelligent rule based feature selection and classification are performed for DoS attack detection in the cloud. The performance of the proposed system has been evaluated on an experimental cloud set up with real time DoS tools. It was observed that the proposed system achieved an accuracy of 98.46% on the experimental data for 10,000 instances with 10 fold cross-validation. By using this methodology, the service providers will be able to provide a more secure cloud environment to the customers.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.3
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• pp.109-119
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• 2019

The purpose of this study is to examine fashion trends and the direction of the four fashion collections by analyzing the design key-words of the four major international fashion collections in 2018. The data of this study was collected by extracting the key-words from Marie Claire Korea in 2018, with the total of the collected data numbering 2,144. The data was analyzed by text mining using the R program and word-cloud, and a co-occurrence network analysis was conducted. The results of this study are as follows: First, the key-words of fashion collection designs in 2018 were fringe and ruffle detail, silk and denim fabric, vivid color, stripe and check pattern, pants suit item, and oversized silhouette, focusing on romanticism and sport. Second, seasonal characteristics of the fashion collections were pastel colors in S/S, primary and vivid colors in F/W. Details were embroidery and cutouts in S/S, patchwork and fringe in F/W. Third, the design trends of the four major fashion collections were presented in the Paris collection: stripes, check patterns, embroidery, lace, tailoring, draping, romanticism, and glamor. In the Milan collection, checks, prints, denim, and minidresses reflected sport and romanticism. The London collection included fringe, ruffles, floral patterns, flower patterns, and romanticism. The New York collections included vivid colors, neon colors, pastel colors, oversize silhouettes, bodysuits, and long dresses.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.7211-7218
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• 2015

Tens of thousands of malicious codes are generated on average in a day. New types of malicious codes are surging each year. Diverse methods are used to detect such codes including those based on signature, API flow, strings, etc. But most of them are limited in detecting new malicious codes due to bypass techniques. Therefore, a lot of researches have been performed for more efficient detection of malicious codes. Of them, visualization technique is one of the most actively researched areas these days. Since the method enables more intuitive recognition of malicious codes, it is useful in detecting and examining a large number of malicious codes efficiently. In this paper, we analyze the relationships between malicious codes and Native API functions. Also, by applying the word cloud with text mining technique, major Native APIs of malicious codes are visualized to assess their maliciousness. The proposed malicious code analysis method would be helpful in intuitively probing behaviors of malware.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.981-993
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• 2018

Smart healthcare is convergence of ICT and healthcare services, and interdisciplinary research has been actively conducted in various fields. The objective of this study is to investigate trends of smart healthcare research using topic modeling and ego network analysis. Text analysis, frequency analysis, topic modeling, word cloud, and ego network analysis were conducted for the abstracts of 2,690 articles in Scopus from 2001 to April 2018. Topic Modeling analysis resulted in eight topics, Topics included "AI in healthcare", "Smart hospital", "Healthcare platform", "Blockchain in healthcare", "Smart health data", "Mobile healthcare", " Wellness care", "Cognitive healthcare". In order to examine the topic modeling results core deeply, we analyzed word cloud and ego network analysis for eight topics. This study aims to identify trends in smart healthcare research and suggest implications for establishing future research direction.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.27-34
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• 2018

This study was conducted to identify the contents of major consulting needs of SMEs using Big Data and to suggest the efficiency of operation. The subjects of the study were counseling cases posted on the website of the Business Support Center of the Ministry of SMEs and Startups. To do this, from 2009 to March 2018, we crawled about 7,000 cases of counseling cases, followed by word cloud analysis centering on effective keyword. The main results were as follows: First, the frequency of counseling cases in each field was found in the order of establishment, management strategy, human resources, financial order. Second, in word cloud analysis, the most frequent keyword related to counseling demand were small businesses, exports, methods, procedures, registration and authentication. In this study, we obtained research results that we can improve the efficiency of the policy in real time from a new point of view by conducting big data analysis on public policy.

• Journal of Korean Library and Information Science Society
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• v.49 no.4
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• pp.265-294
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• 2018

Nowadays, due to an explosive increase in information, information filtering is very important to provide proper information for users. Users hardly obtain scholarly information from a huge amount of information in NDSL of KISTI, except for simple search. In this paper, we propose the service, PIN to solve this problem. Pin provides the word cloud including analyzed users' and others' interesting, co-occurence, and searched keywords, rather than the existing word cloud simply consisting of all keywords and so offers user-customized papers, reports, patents, and trends. In addition, PIN gives the paper classification in NDSL according to keyword matching based classification with the overlapping classification enabled-academic classification system for better search and access to solve this problem. In this paper, Keywords are extracted according to the classification from papers published in Korean journals in 2016 to design classification model and we verify this model.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.33-38
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• 2021

The convergence trend is the core of the 4th industrial revolution, and due to such expectations and possibilities, various countermeasures are being sought in diverse fields. This study conducted a quantitative analysis to identify the trend of convergence research over the past 10 years. Specifically, major research keywords were extracted, word cloud techniques were applied, and visualized to identify trends in academic research on convergence. To this end, research papers from 2012 to 2020 published in journal of digital convergence were investigated. The analysis period was divided into two periods: the former 4 years(2012-2015) and the latter 4 years(2016-2019) to confirm the difference in research trends. In addition, the research papers of 2020 were analyzed in order to more clearly understand the changes in the research trend of the last year due to the COVID-19. The results of this study are significant in that they can be used as useful basic data for future research and to understand research trends as keywords in the field of convergence.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.574-581
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• 2024

This study explores the usability of extended reality (XR) content tailored for production process training, with a focus on user experience. Participants engaged with extended reality training modules, and qualitative data was subsequently collected through interviews. These interviews evaluated the hardware, user interface, and overall user satisfaction. The analysis utilized python packages for keyword extraction and word cloud visualization, offering insights into user perceptions. The findings revealed that although the hardware was deemed comfortable, concerns were raised regarding its weight and heat emission. The interactive interface, which relies on hand tracking, encountered issues with recognition rates, leading to suggestions for alternative input methods. Users acknowledged extended reality's potential impact on industries like healthcare and education, sharing both positive and negative views on the technology. This research enhances our understanding of user responses and guides the future enhancement of extended reality content for industrial applications, aiming to improve its quality and practical usability