• Journal of Digital Convergence
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• v.14 no.10
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• pp.95-105
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• 2016

Recently the problem of child abuses has become a big social issue. According to national statistics data portal, the population under 19 years old is shrinking trend, but the number of child abuse is increasing day ever. However, the number of counseling after calling is a constant level without large fluctuations. Due to the seriousness of the problems, child abuse is even worse despite the research and countermeasures. This study designed a study model on the child abuse based on a preliminary study and suggested plans for reducing child abuse through the big data analytics. When we see a result of test of the hypothesis, abuse actor characteristics, characteristics of children, and employment type were analyzed to have a significant impact on child abuse. Based on such analysis, this research has suggested ways to reduce child abuse, including educational and economic support measures.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.1-8
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• 2019

The purpose of this study is to analyze the employment trends of autonomous automobile industry which is related to the 4th Industrial Revolution. Previously, big data of the employment trends were divided into skill field and task field. As a result, if a company was employed in the field of skill field, it was required to have talent in which personality traits and innovation traits were prominent. Second, if the task field is a production worker, it is desirable to have talented person with outstanding personality traits. In addition, if the task field is management, it has been confirmed that communication qualities require outstanding talent. The results of this study suggest that it is possible to use the data as a basic data for finding an effective employment strategy by identifying the characteristics of the talented person and considering the suitability of the tendency of hiring.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.231-238
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• 2021

SNS data can catch the user's thoughts and actions. And the trend of the search portal is a representative service that can observe the interests of users and their changes. In this paper, the relationship was analyzed by comparing statistics on narcotics incidents and the degree of exposure to narcotics related words in tweets of SNS and in the trends of search portal. It was confirmed that the trend of SNS and search portal trends was the same in the statistics of the prosecution office with a certain time difference.In addition, cluster analysis was performed to understand the meaning of tweets in which narcotics related words were mentioned. In the 50,000 tweets collected in January 2020, it was possible to find meaning related to the sale of actual drugs. Therefore, through SNS monitoring alone it is possible to monitor narcotics-related incidents and to find specific sales or purchase-related information, and this can be used in the investigation process. In the future, it is expected that crime monitoring and prediction systems can be proposed as related crime analysis may be possible not only with text but also images.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.589-591
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• 2018

인터넷이 발달함에 따라 데이터의 생산량은 기하급수적으로 증가하고 있고, 생성된 막대한 양의 데이터를 사용하는 목적에 맞게 분석하여 이익이 될 수 있는 유의미한 정보를 얻을 수 있다. 본 논문에서는 빅 데이터 분석을 위한 여러 가지 기술들과 분석 플랫폼 동향을 알아보고, 국내에서 빅 데이터가 발전하기 위한 방안에 대해서 알아본다.

• Journal of the Korean Society for information Management
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• v.37 no.2
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• pp.171-195
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• 2020

This study analyzed the collaborative process in time series by dismantling the edit log big data of Wikipedia Korea, a representative online collaboration community, from early 2002 to 2019. Analysis elements were extracted from the document edit records, formatted in standardized XML, and analyzed using Python and R. The ways of editors' contribution, the characteristics of data contents, and the trend of document creation were explained by the analysis. An active contribution of a small set of editors and a loose participation of the majority were revealed. In addition, sociocultural characteristics that appear in online communities were also found in Wikipedia Korea. A new, diverse set of external resources is necessary to sustain the collective intelligence. An effort to settle new editors into the wikipedia community and an openness through circulation structure to avoid the exclusiveness of the management group are suggested.

• Journal of Korean Library and Information Science Society
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• v.50 no.1
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• pp.23-41
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• 2019

This study understand the subject domain of book which has been read by men and woman elderly by analizying the PFNET using library big data and confirm the difference between adult at age 30-40. This study extract co-occurrence matrix of book lending on the popular book list from library big data, for 4 group, men/woman elderly, men/woman adult. With these matrix, this study performs FP network analysis. And Pearson Correlation Analysis based on the Triangle Betweenness Centrality calculated on the loan book was performed to understand the correlation among the 4 clusters which has been created by PNNC algorithm. As a result, reading trend which has been focused on modern korean novel has been revealed in elderly regardless gender, among them, men elderly show extreme tendency concentrated on modern korean long series novel. In the correlation analysis, the male elderly showed a weak negative correlation with the adult male of r = -0.222, and the negative direction of all the other groups showed that the tendency of male elderly's loan book was opposite.

• Journal of The Korean Association of Information Education
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• v.21 no.1
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• pp.57-66
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• 2017

Lately, academic interests in big data analysis and social network has been prominently raised. Various academic fields are involved in this social network based research trend, which is, social network has been actively used as the research topic in social science field as well as in natural science field. Accordingly, this paper focuses on the text analysis and the following social network analysis with the Master's and Doctor's dissertations. The result indicates that certain words had a high frequency throughout the entire period and some words had fluctuating frequencies in different period. In detail, the words with a high frequency had a higher betweenness centrality and each period seems to have a distinctive research flow. Therefore, it was found that the subjects of the Master's and Doctor's dissertations were changed sensitively to the development of IT technology and changes in information curriculum of elementary, middle and high school. It is predicted that researches related to smart, mobile, smartphone, SNS, application, storytelling, multicultural, and STEAM, which had an increased frequency in period 4, would be continuously conducted. Moreover, the topics of robots, programming, coding, algorithms, creativity, interaction, and privacy will also be studied steadily.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.183-189
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• 2022

COVID-19 is also influencing the coffee industry. This will increase untact consumption, a new consumption trend. Consumption utilizing online channels and delivery service applications that represent untact consumption is becoming commonplace. The coffee industry is also increasingly using coffee shops with drive-through and smart ordering systems that can be ordered with minimal contact. While most of the untact services are preempted at franchise stores, many independent coffee shops still offer differentiated services by communicating directly with customers. However, along with the prolonged COVID-19 infection, coffee shops in the present era, which cannot be free from infectious diseases, have no choice but to worry about delivery services. Therefore, this study analyzed the factors that influence coffee delivery services. Research results due to the influence of COVID-19, regular delivery services have increased along with coffee delivery services. Regular delivery services will play a central role in coffee delivery services due to increased use of home cafes by consumers who want to enjoy coffee in various ways.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.59-64
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• 2019

This study used the Google Trends site to analyze selection information that users expect from prominent Toothbrushes and Toothpastes through related search keywords that users wanted to obtain. From 2006 to 2018(sep), searches for Toothbrushes and Toothpastes were arranged in the order of popularity of related searched words. The total number of searches words exposed was each 25, total 325 collected. The analysis was conducted using two methods, first, by search function. second, by a word network using a Big Data program. The study has shown that toothbrushes there are high expectations for brands, toothpaste there are high expectations in the function. In order to increase the motivation for oral health education, it is recommended to use and provide knowledge about the brand of toothbrushes and Toothpastes by the function.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.893-895
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• 2016

Data center has a lot of management efforts for the facility, energy, and efficient usage monitoring. Data center power management is important to make the data center have reliable service and cost-effective business. In this paper, IoT based energy measurements monitoring which gives support to energy consumption analysis including indoor, outdoor temperature condition. This converged information for energy analysis gives various aspects of energy consumption effects. With IoT big data, energy machine learning system can give the relation of energy components and measurements, it is the key information of the quick energy analysis in the just one month data trend for the prediction and estimation.