• The Journal of Information Systems
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• v.28 no.3
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• pp.105-121
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• 2019

Purpose One of the reasons for the expansion of information systems in the enterprise is the increased efficiency of data analysis. In particular, the rapidly increasing data types which are complex and unstructured such as video, voice, images, and conversations in and out of social networks. The purpose of this study is the customer needs analysis from customer voices, ie, text data, in the web environment.. Design/methodology/approach As previous study results, the word frequency of the sentence is extracted as a word that interprets the sentence has better affects than frequency analysis. In this study, we applied the TF-IDF method, which extracts important keywords in real sentences, not the TF method, which is a word extraction technique that expresses sentences with simple frequency only, in Korean language research. We visualized the two techniques by cluster analysis and describe the difference. Findings TF technique and TF-IDF technique are applied for Korean natural language processing, the research showed the value from frequency analysis technique to semantic analysis and it is expected to change the technique by Korean language processing researcher.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.47-56
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• 2022

With the advent of online platforms, individuals have been able to trade small resources, such as a room, in the market. However, as there is no clear regulation on these economic activities, various side effects have emerged. Accordingly, the government reestablished related policies to resolve the unintended consequences of these economic activities. However, the policy has not been implemented yet, and many participants do not comply with the policy. Therefore, this study intends to examine their perceptions in detail. For this purpose, a text mining technique was applied. Posts and comments from major online communities were collected. By applying the topic modeling technique, 5 topics were derived. Compliance with the government's policy is a voluntary decision. Therefore, it is necessary to carry out an in-depth understanding of the policy target. Therefore, based on this study, it is expected that in the future, methods to induce them to conform to policy can be discussed in detail.

• Spatial Information Research
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• v.22 no.4
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• pp.11-20
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• 2014

This study aims to provide information about the research-trends in the area of Geospatial Information using text-mining methods. We derived the National R&D Reports and papers from NDSL(National Discovery for Science Leaders) site. And then we preprocessed their key-words and classified those in separable sectors. We investigated the appearance rates and changes of key-words for R&D reports and papers. As a result, we conformed that the researches concerning applications are increasing, while the researches dealing with systems are decreasing. Especially, with in the framework of the keyword, '3D-GIS', 'sensor' and 'service' xcept ITS are emerging. It could be helpful to investigate research items later.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.10-23
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• 2016

With requiring circumspections using big data, this study attempts to develop and apply the search method for audit issues relating to the ITS policy or program. For the foregoing, the auditing process of the board of audit and inspection was converged with the theoretical frame of boundary analysis proposed by William Dunn as an analysis tool for audit issues. Moreover, we apply the text mining technique in order to computerize the analysis tool, which is similar to the boundary analysis in the concept of approaching meta-problems. For the text mining analysis, specific model we applied the antisymmetry-symmetry compound lexeme-based LDA model based on the Latent Dirichlet Allocation(LDA) methodologies proposed by David Blei. The several prime issues were founded through a case analysis as follows: lack of collection of traffic information by the urban traffic information system, which is operated by the National Police Agency, the overlapping problems between the Ministry of Land, Infrastructure and Transport and the Advanced Traffic Management System and fabrication of the mileage on digital tachograph.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.87-97
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• 2018

The traffic accident reports that are generated by the Traffic Broadcasting Networks(TBN) are unstructured data. It, however, has the value as some sort of real-time traffic information generated by the viewpoint of the drives and/or pedestrians that were on the roads, the time and spots, not the offender or the victim who caused the traffic accidents. However, the traffic accident reports, which are big data, were not applied to traffic accident analysis and traffic related research commonly. This study adopting text-mining technique was able to provide a clue for utilizing it for the impacts of traffic accidents. Seven years of traffic reports were grasped by this analysis. By analyzing the reports, it was possible to identify the road names, accident spot names, time, and to identify factors that have the greatest influence on other drivers due to traffic accidents. Authors plan to combine unstructured accident data with traffic reports for further study.

• The Journal of Bigdata
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• v.1 no.2
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• pp.21-34
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• 2016

There are various investment strategy reports available online, prepared by many financial analysts. If the correlation between the title of the report and analyst forecast can be found, we can tell from the title whether analyst' forecast will be reliable or not. The objective of this study is to see the correlation between the title of analyst investment strategy report and the actual result of forecast by using the Text Mining technique. The result of actual analysis showed that "strong buy and sell call" appeared in the title lead the higher accuracy of analyst forecast and fulfillment ratio. The results that potential investors can get better information by reading the title of the analyst report. We hope that this study could be the basis for new methodologies in this area.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.249-275
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• 2016

For the past 50 years, innovation field has gone through an evolution. The range of research topics on innovation has expanded and diversified, along with a quantitative increase. In a multi-disciplinary field like innovation, to explore new topics and understand research trends, it is necessary to possess a comprehensive understanding regarding the current status of, and trends in, the research. In this study, the research trend in innovation studies from 2000 to 2015 was analyzed in a holistic perspective. For this, a novel technique, text mining was used. The result shows that innovation studies has focused on the traditional and emerging topics. Also, the differentiations has appeared in some of the traditional topics. This study provides not only an understanding of research dynamics, but also an opportunity to gain insights into the evolution of a new paradigm from an academic perspective.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.595-607
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• 2021

Purpose: This study introduces a systematic framework to evaluate service satisfaction of cosmetic brands through online review analysis utilizing Text-Mining technique. Methods: The framework assumes that the service satisfaction is evaluated by positive comments from online reviews. That is, the service satisfaction of a cosmetic brand is evaluated higher as more positive opinions are commented in the online reviews. This study focuses on two approaches. First, it collects online review comments from the top 50 global cosmetic brands and evaluates customer service satisfaction for each cosmetic brands by applying Sentimental Analysis and Latent Dirichlet Allocation. Second, it analyzes the determinants that induce or influence service satisfaction and suggests the guidelines for cosmetic brands with low satisfaction to improve their service satisfaction. Results: For the satisfaction evaluation, online review data were extracted from the top 50 global cosmetic brands in the world based on 2018 sales announced by Brand Finance in the UK. As a result of the satisfaction analysis, it was found that overall there were more positive opinions than negative opinions and the averages for polarity, subjectivity, positive ratio, and negative ratio were calculated as 0.50, 0.76, 0.57, and 0.19, respectively. Polarity, subjectivity and positive ratio showed the opposite pattern to negative ratio, and although there was a slight difference in fluctuation range and ranking between them, the patterns are almost same. Conclusion: The usefulness of the proposed framework was verified through case study. Although some studies have suggested a method to analyze online reviews, they didn't deal with the satisfaction evaluation among competitors and cause analysis. This study is different from previous studies in that it evaluates service satisfaction from a relative point of view among cosmetic brands and analyze determinants.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.79-88
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• 2022

Social media big data includes a lot of information that can identify not only consumer consumption patterns but also local images. This paper was collected annually data including 'Samcheok' from 2015 to 2019 from Blog and Cafe of Naver and Daum in domestic portal site, and analyzed the regional image change after refining keyword which forms the regional image by performing text mining and network analysis. According to the research results, the regional image of 2015 was expressed with image cognitive elements of the nearby place name or place etc. such as 'Jangho Port', 'Donghae', and 'Beach'. However the regional image both 2016 and 2019 were changed with image cognitive elements of 'SamcheokSolbich' which is a special place within region. Therefore as the keywords related to the local image include 'Jangho Port' and Resort, which are the representative attractions of Samcheok, it can be seen that the infrastructure factor plays a big role in forming the local image. The significance test for the network data used the bootstrap technique, and the p-values in 2015, 2016, and 2019 were 0.0002, 0.0006, and 0.0002, respectively, which were found to be statistically significant at the significance level of 5%.

• Journal of Engineering Education Research
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• v.25 no.5
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• pp.85-93
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• 2022

Capstone Design, a project-based learning technique, is the most important curriculum that clarifying major knowledge and cultivating the ability to apply through the process of solving problems in the industrial field centered on the student project team. Accordingly, various and extensive studies are being conducted for the successful implementation of capstone design courses. Unlike previous studies, this study aimed to quantitatively analyze the opinions that recorded the experiences and feelings of students who performed capstone design, and used text mining methodologies such as frequency analysis, correlation analysis, topic modeling, and sentiment analysis. As a result of examining the overall opinions of the latter period through frequency analysis and correlation analysis, there was a difference between the languages used by the students in the opinions according to gender and project results. Through topic modeling analysis, 'topic selection' and 'the relationship between team members' showed an increase in occupancy or high occupancy, and topics such as 'presentation', 'leadership', and 'feeling what they felt' showed a tendency to decreasing occupancy. Lastly, sentiment analysis has found that female students showed more neutral emotions than male students, and the passed group showed more negative emotions than the non-passed group and less neutral emotions. Based on these findings, students' practical recognition of the curriculum was considered and implications for the improvement of capstone design were presented.