• The Journal of the Korea Contents Association
• /
• v.21 no.11
• /
• pp.785-792
• /
• 2021

Since the Fourth Industrial Revolution, various changes have occurred in society as a whole due to advance in technologies such as artificial intelligence and big data. The amount of data that can be collect in the process of applying important technologies tends to increase rapidly. Especially in academia, existing generated literature data is analyzed in order to grasp research trends, and analysis of these literature organizes the research flow and organizes some research methodologies and themes, or by grasping the subjects that are currently being talked about in academia, we are making a lot of contributions to setting the direction of future research. However, it is difficult to access whether data collection is necessary for the analysis of document data without the expertise of ordinary programs. In this paper, propose a text mining-based topic modeling Web application model. Even if you lack specialized knowledge about data analysis methods through the proposed model, you can perform various tasks such as collecting, storing, and text-analyzing research papers, and researchers can analyze previous research and research trends. It is expect that the time and effort required for data analysis can be reduce order to understand.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.6 no.8
• /
• pp.399-408
• /
• 2016

As entering the Big Data age, utilization of Big Data is also increasing in the intellectual property sector. Meanwhile, the purpose of a trademark which distinguishes the source of the goods essentially is to enable the public to recognize the goods. Big Data technologies which is recently becoming a issue can be used as a tool to judge consumer's awareness of the trademark. It was difficult for judgment of trademark awareness through traditional ways. As a new way, survey methodology has bee received attention, and it was applied to the field of trademark law. However, various problems such as cost, time, objectivity, and fairness were observed. In order to overcome theses limitations, this study proposes new way utilizing big data analytics for judgment on consumer's awareness of the trademark. This new way will not only contribute to enhancing the objectivity of judging trademark awareness but also utilized to support for related legal judgments.

• Information Systems Review
• /
• v.22 no.3
• /
• pp.157-172
• /
• 2020

The demand of information security consultants is expected to increase due to the emergence of ISMS-P incorporating ISMS and PIMS, the implementation of European Privacy Act (GDPR) and various security accidents. In this paper, we collected and analyzed advertisements of job advertisement sites that could identify firms' demand explicitly. We selected representative job advertisement sites in Korea and the United States and collected job advertisement details of information security consultants in 2014 and 2019. The collected data were visualized using text mining and analyzed using non-parametric methods to determine whether there was a change in the role of the information security consultant. The findings show that the requirements for information security consultants have changed very little. This means that the role does not change much over a five year time gap. The results of the study are expected to be helpful to policy makers related to information security consultants, those seeking to find employment as information security consultants, and those seeking information security consultants.

• Journal of the Korean Society for information Management
• /
• v.41 no.1
• /
• pp.107-132
• /
• 2024

This study attempted to analyze newspaper articles related to May 18 through frequency analysis and network analysis using news data related to May 18 for about 30 years from 1990 to 2022 at the Korea Press Foundation's Big Kinds. Specifically, quantitative change trends were examined by analyzing the amount of articles by period and region, and the connection structure between major keywords by the regime was explored through network analysis by regime using co-appearance keywords. As a result of the analysis, it was found that 2019 had the largest amount of coverage, which had many social issues in time, and the Jeolla-do region had the largest amount of coverage in the region. And as a result of network analysis, there were differences in words related to May 18 in news data according to the perception and policy of the regime toward May 18. As a result of synthesizing the analysis of May 18 news data, it was confirmed that May 18 was becoming a democratic movement over time regardless of region, but at the same time, the distortion of May 18 was not resolved.

• Information Systems Review
• /
• v.18 no.3
• /
• pp.73-96
• /
• 2016

Recent research on information and communication technology and Internet-of-Things indicates that convergence and integration facilitate the development of various technologies. Similarly, related academic theories and technologies have also gained attention. This paradigm shift facilitated the convergence and integration of academic disciplines. In particular, information systems have become initiators of change. However, only a limited number of studies have been conducted on information systems. To address this gap, this study explores the future direction of information systems based on the core concepts and results of the comparative analysis conducted on research trends. We considered 48,102 data obtained from international top journals from 1980 to 2015. We analyzed journal titles, authors, abstracts, and keywords. We conducted the network analysis on existing collaborative studies and performed comparative analysis to visualize the results. The results provide an in-depth understanding of information systems and provides directions for future research on this area.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.48 no.1
• /
• pp.35-45
• /
• 2020

This study focused on the park as a space to support the behavior of urban citizens in modern society. Modern city parks are not spaces that play a specific role but are used by many people, so their function and meaning may change depending on the user's behavior. In addition, current online data may determine the selection of parks to visit or the usage of parks. Therefore, this study analyzed the change of behavior in Yeouido Park, Yeouido Hangang Park, and Yangjae Citizen's Forest from 2000 to 2018 by utilizing a time series analysis. The analysis method used Big Data techniques such as text mining and social network analysis. The summary of the study is as follows. The usage behavior of Yeouido Park has changed over time to "Ride" (Dynamic Behavior) for the first period (I), "Take" (Information Communication Service Behavior) for the second period (II), "See" (Communicative Behavior) for the third period (III), and "Eat" (Energy Source Behavior) for the fourth period (IV). In the case of Yangjae Citizens' Forest, the usage behavior has changed over time to "Walk" (Dynamic Behavior) for the first, second, and third periods (I), (II), (III) and "Play" (Dynamic Behavior) for the fourth period (IV). Looking at the factors affecting behavior, Yeouido Park was had various factors related to sports, leisure, culture, art, and spare time compared to Yangjae Citizens' Forest. The differences in Yangjae Citizens' Forest that affected its main usage behavior were various elements of natural resources. Second, the behavior of the target areas was found to be focused on certain main behaviors over time and played a role in selecting or limiting future behaviors. These results indicate that the space and facilities of the target areas had not been utilized evenly, as various behaviors have not occurred, however, a certain main behavior has appeared in the target areas. This study has great significance in that it analyzes the usage of urban parks using Big Data techniques, and determined that urban parks are transformed into play spaces where consumption progressed beyond the role of rest and walking. The behavior occurring in modern urban parks is changing in quantity and content. Therefore, through various types of discussions based on the results of the behavior collected through Big Data, we can better understand how citizens are using city parks. This study found that the behavior associated with static behavior in both parks had a great impact on other behaviors.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.6
• /
• pp.2021-2029
• /
• 2010

This paper suggested the method to design and analyze FMC robot's dispatching rule using the Simulation and Sequential Patterns. To do this, first of all, we built FMC using simulation and then, extracted signals that facilities call a robot, saved it as the log type. Secondly, we built robot's optimal path using the Sequential Pattern Mining with the results of analyzing the log and relationship between machine and robot actions. Lastly, we adapted it to the A corp.'s manufacturing line for verifying its performance. As a result of applying the new dispatching rule in FMC, total throughput and total flow time decrease because of decreasing material loss time and increasing robot utility. Furthermore, because this method can be applied for every manufacturing plant using simulation, it can contribute to advance total FMC efficiency as well.

• Cartoon and Animation Studies
• /
• s.36
• /
• pp.553-572
• /
• 2014

In this paper, for the evaluation of the ease of a particular Web site (www.appbelt.net), insert the log tracking code for Google Analytics in a page of the Web site to collect behavioral data of visitor and has studied the improvement measures for the problems of the Web site, after the evaluation of the overall quality of the Web site through the evaluation of Coolcheck. These findings set the target value of the company's priority (importance) companies want to influence the direction of the business judgment are set up correctly, and the user's needs and behavior will be appropriate for the service seems to help improvement.

• Journal of Technology Innovation
• /
• v.26 no.4
• /
• pp.146-172
• /
• 2018

In the Small and Medium Enterprises(SMEs) sector, research has shown an increasing trend due to changes in industrial society and policy. Therefore, the interrelationship between academic research and policy is relatively high. In this study, we analyzed the trends of academic research related to SMEs innovation policy. Moreover, we examined the interrelationships. By using text mining techniques, we have identified key themes and changes in domestic policy papers published since the announcement of the "Five-Year Plan for Innovation of SMEs". Also, we compared them with "Five-Year Plan for Innovation of SMEs" of each period. The result shows that the gap between academic research and policy has been closing over time. This study shows that there is an increasing number of research studies that verify policies at the relevant time from an academic point of view, and that policy issues are in turn influencing academic research due to government-driven policies. Also, it was confirmed that there was a time gap between academic research and policy. Academic research tended to increase compared to the previous year's level, when the policy had been implemented. The results of this study are expected to contribute to the establishment of the "2019~2023 five-year plan for Small and Medium Enterprises" which will be announced in the future, and this study will demonstrate the possibility of devising evidence-based policy.

• The Korean Journal of Applied Statistics
• /
• v.32 no.1
• /
• pp.111-128
• /
• 2019

Subways are eco-friendly public transportation that can transport large numbers of passengers safely and quickly. It is necessary to predict the accurate number of passengers in order to increase public interest in subway. This study groups stations on Lines 1 to 9 of the Seoul Metropolitan Subway using clustering analysis. We propose one final prediction model for all stations and three optimal prediction models for each cluster. We found three groups of stations out of 294 total subway stations. The Group 1 area is industrial and commercial, the Group 2 ares is residential and commercial, and the Group 3 area is residential districts. Various data mining techniques were conducted for each group, as well as driving some influential factors on demand prediction. We use our model to predict the number of passengers for 8 new stations which are part of the 3rd extension plan of Seoul metro line 9 opened in October 2018. The estimated average number of passengers per hour is from 241 to 452 and the estimated maximum number of passengers per hour is from 969 to 1515. We believe our analysis can help improve the efficiency of public transportation policy.