• Journal of Digital Convergence
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• v.17 no.11
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• pp.61-70
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• 2019

The The government has recently announced its mid- to long-term plans for promoting art. With the advent of the 4th industrial revolution, contemporary art contents that are integrated with Intelligent Information Technologies such as Artificial Intelligence (AI), Virtual Reality (VR), and Big Data are being introduced, and social interest in humanities and creative convergence is rising. In addition, the industrialization of the art market is expanding amid the rising popularity of art among the general public and the growing interest of art as an investment replacement system, along with the strengthening of the creative personality education of our Education Ministry. Therefore, it is necessary to establish a strategy for transparency and revitalization of the art market by providing comprehensive information such as search functions, analysis data, and criticism by writer and price. This paper has established an information system plan for the establishment of an online supply system for art transaction information, providing auction transaction information for art market, providing report and news for art market, providing public relations platform, and providing art market analysis service and membership relationship management service. To this end, the future model was established through environmental analysis and focus analysis of the art market, and strategic tasks and implementation plans were established accordingly.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.123-141
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• 2021

As the dependence of technology on the economic structure increases, the importance of National Core Technology is increasing. However, due to the nature of the technology itself, it is difficult to determine the scope of the technology to be protected because the scope of the relation is abstract and information disclosure is limited due to the nature of the National Core Technology. To solve this problem, we propose the most appropriate literature type and method of analysis to distinguish important technologies related to National Core Technology. We conducted a pilot test to apply TF-IDF, and LDA topic modeling, two techniques of text mining analysis for big data analysis, to four types of literature (news, papers, reports, patents) collected with National Core Technology keywords in the field of Display industry. As a result, applying LDA theme modeling to patent data are highly relevant to National Core Technology. Important technologies related to the front and rear industries of displays, including OLEDs and microLEDs, were identified, and the results were visualized as networks to clarify the scope of important technologies associated with National Core Technology. Throughout this study, we have clarified the ambiguity of the scope of association of technologies and overcome the limited information disclosure characteristics of national core technologies.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.376-387
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• 2021

This study is to analyze the research trends related to the 'glass ceiling' phenomenon using big data analysis methods and to suggest social implications. To analyze the research trends of 'glass ceiling', the historical event that broke the 'glass ceiling' was set as an important issue, and keywords were collected by dividing park's term into three. Before, throughout and after, her term. As a result of frequency analysis, research was conducted based on 'public servants' which was selected as the main keyword in the first period, while 'women's work family compatibility' was chosen as the main keyword group in the second period. In the third period, keywords for women's occupational groups were being diversified. As a result of applying CONCOR techniques to make the studied main topics grouped, we were able to confirm that the main issues were the differentiating factors, the customary gender discrimination culture, the jobs aimed for studying, the work-family balance, the glass ceiling and the organizational performance adjustment factors, the public sector, organizational performance, and the private sector. Besides work-family compatibility support system, it was suggested as a social implication that research on improving the system to resolve the glass ceiling factor and to expand the target jobs to give solutions to real-life issues were needed, and also suggested that research on the 'glass ceiling' which the general public perceives through social medias or articles in the news, was needed in the future.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.199-204
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• 2022

The purpose of this study is to broaden the understanding of the Security Services Industry Act, and also to examine the meanings of various phenomena by analyzing the media report big data rather than the researchers' perspective on the Security Services Industry Act. In the research method, this study searched for a keyword 「Security Services Industry Act」 that prescribes the security work as an important subject of crime prevention and maintenance of public order in Korea. The data was searched from 1990 to 2021 the BIG KINDS could provide. Also, for the concrete analysis during the period of data search, it was divided into settlement period(1976~2001), growth period-quantitative(2002~2012), and growth period-qualitative(2013~2021). In the results of this study, the media report perception of the Security Services Industry Act is continuously emphasizing the social roles and importance of private security according to the flow of time. The consequent marketability of private security will play great roles in the protection of people's lives and properties in the combination with various other industries in the future. However, the private security industry that provides public peace service together with the police, could be rising as an element that hinders the development of private security industry because of various social issues caused by legal regulations and illegal problems, so it would be necessary to more strengthen its responsibility and roles accordingly.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.11-19
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• 2016

SNS users are continuously increasing and SNS is emerging as a major PR channel of government. In particular, SNS can be a useful tool, but also the challenges for risk communication. This study is examined how nuclear regulatory organizations' SNS management and visitors' responses to the facebook pages in Korea and U.S.. Results indicated that both organizations frequently used information-oriented posting. Concerning the types of PR, NSSC tended to mainly use 'Relationship-Management PR', NRC mainly use 'Image PR.' In addition, our analyses on visitors' responses showed that visitors usually in response to participational and visual(ex. video, card news) typed contents. Based on its' results, this study provides practical suggestions for government's future SNS management strategies.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.379-388
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• 2014

This study analyzed the status of Korean professional baseball as TV contents utilizing ratings. For the purpose of the study, Korea professional baseball's relative status to other genres though ratings is investigated. For this study, ratings per minute for the whole cable TV channel viewer ratings in 2010 were analyzed, and the following is the result of comparing and analyzing ratings per genre and channel of cable TV. Among 11 genres, drama showed the highest rating, and entertainment, movies, kids, news/reports, sports, music, etc followed. Drama and entertaining channels showed the highest ratings and sports did not show any high ranking. However, when analyzing times for broadcasting Korean professional baseball separately, Korean professional baseball in both genre and channel showed the highest r ratings and it was significant statistically. Thus, it is considered that Korean professional baseball is the most valuable contents for the related cable TV times.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.241-255
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• 2020

The purpose of this study is to analyze musical performances with the use of performance booking information from 2017 to 2019 which was obtained in Korea performing Arts Box Office Information system (KOPIS), and to make suggestions of Korean musical performances. Based on the data of KOPIS, relevant studies, internet based information, news articles, and magazines, musical performances were analyzed. In addition, the previous data of KOPIS and the data of the Broadway League were analyzed. The analysis results are as follows. Firstly, it is necessary to concentrate on Korean mid-sized theatre musical performances. Secondly, producers need to open their production costs invested in performances transparently. Thirdly, Off-Broadway system needs to be introduced after being modified in consideration of Korean situations. Thirdly, it is necessary to make long-run performances in order to achieve commercial success. Fifthly, it is necessary to make a bold attempt of theatre for performances just as in Broadway.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.423-430
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• 2016

The purpose of this paper is to explore and analyze design of USATODAY.COM aimed at being helpful for Chinese online news industry to search for the way forward. USATODAY.COM which converges print and online newsrooms is regarded as a pioneer in the online communication media. It engages interaction with users and their demand, and provides the best level of website and service design. This paper conducted through both theoretical works and design analyses by randomly visiting USATODAY.COM from May 23 to June 5, 2016. USATODAY.COM maintains consistent and high quality of a visual identity system on its homepage, and it is strongly linked to that of USA TODAY. Also, USATODAY.COM provides unique content provision methods, interactive features, advertisement and payment functions through service design considering the user experiences and needs. Based on its results, it is expected to contribute to Chinese online newspaper market which has an astonishing chance to grow.