• International conference on construction engineering and project management
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• 2020.12a
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• pp.433-439
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• 2020

As eco-friendly and sustainable architecture is becoming more popular, the interest in Korean traditional wooden buildings (Hanok) has also been increasing. The building technologies of the wooden construction have been actively developed in all over the world through the diversification of new materials and construction methods. On the other hand, the growth rate of wooden construction market is still slow in Korea. In an attempt to promote the Korean traditional wooden buildings, a comprehensive research project has been conducted. This R&D project is developing standard designs, new materials, and methods for modernized Hanok including houses, public buildings, long-span structures, and even high-rise buildings. To this end, the purpose of this study is to formulate a technological strategy for popularization of modernized Hanok. Influencing variables and issues are analyzed and defined first. At the same time, the five keywords have examined in the perspective of dissemination of modernized Hanok technology. Finally, a technology road map for strategic development of modernized Hanok is proposed through casual diagrams.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.1-18
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• 2012

This paper identifies technology trends of national research and development (national R&D) by exploiting Korean national R&D patents, ranging from 2007 to 2010. In this paper, co-word analysis (CWA), which is a method to identify the relationship among technology terms by using their co-occurrences, is incorporated into network analysis to visualize the relationships among technology keywords of national R&D patents and calculate network indexes concerning inter-relationship diversity and strength of technology keywords. As a result, this research found that inter-relationship among technology keywords in national R&D are getting increasingly strengthening in an overall sense. In addition, the keyword inter-relationship diversity-strength map proposed in this paper revealed some significant technological keywords of national R&D : core technology keywords including "sensor", "film" and "fuel" and emerging keywords including "biosensor" and "thermoelectric". Because the proposed approach helps identify interdisciplinary trends of technology keywords from a massive volume of national R&D patents in a visual and quantitative way, we expect that the approach can be incorporated as a preliminary into the R&D planning process to assist R&D policy makers to understand technology convergence of national R&D and develop relevant R&D policies.

• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.83-103
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• 2015

The rapid development of internet technologies and social media over the last few years has generated a huge amount of unstructured text data, which contains a great deal of valuable information and issues. Therefore, text mining-extracting meaningful information from unstructured text data-has gained attention from many researchers in various fields. Topic analysis is a text mining application that is used to determine the main issues in a large volume of text documents. However, it is difficult to identify related issues or meaningful insights as the number of issues derived through topic analysis is too large. Furthermore, traditional issue-clustering methods can only be performed based on the co-occurrence frequency of issue keywords in many documents. Therefore, an association between issues that have a low co-occurrence frequency cannot be recognized using traditional issue-clustering methods, even if those issues are strongly related in other perspectives. Therefore, in this research, a methodology to reorganize social issues from a research and development (R&D) perspective using social network analysis is proposed. Using an R&D perspective lexicon, issues that consistently share the same R&D keywords can be further identified through social network analysis. In this study, the R&D keywords that are associated with a particular issue imply the key technology elements that are needed to solve a particular issue. Issue clustering can then be performed based on the analysis results. Furthermore, the relationship between issues that share the same R&D keywords can be reorganized more systematically, by grouping them into clusters according to the R&D perspective lexicon. We expect that our methodology will contribute to establishing efficient R&D investment policies at the national level by enhancing the reusability of R&D knowledge, based on issue clustering using the R&D perspective lexicon. In addition, business companies could also utilize the results by aligning the R&D with their business strategy plans, to help companies develop innovative products and new technologies that sustain innovative business models.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.2
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• pp.1-22
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• 2016

While many organizations believe that cloud computing has the potential to reduce operational cost by abstracting capital assets like data storage center and processing systems into a readily on demand available and affordable operating expenses, still many of these organizations are not aware of the factors determining the performance of cloud computing technology. This paper provides a systematic literature review focusing on the factors determining the performance of cloud computing. In trying to come up with this review, the following sources were searched for relevant articles: ScienceDirect, Scientific.Net, ACMDigital Library, IEEE Xplore, Springer, World Scientific Journal, Wiley Online Library, Academic Search Premier (via EBSCOHost) and EdITLib (Education & Information Technology Digital Library). In first search strategy, approximately 100 keywords related to the research domain like; "Cloud Computing" and "Cloud Services" were used. In second search strategy, 65 keywords more related to the research domain were selected. In the third search strategy, the primary materials were identified and classified according to the paper types (Journal or Conference), year of publication and so on. Based on this study, twenty (20) factors were found that determine the performance of cloud computing. The IT organization needs to consider these twenty (20) factors in order to adopt cloud computing.

• Journal of Information Technology Applications and Management
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• v.30 no.4
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• pp.77-86
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• 2023

This study conducted sentiment analysis on Hong Kong cinema from two distinct eras, pre-2000 and post-2000, examining audience preferences by comparing keywords from movie reviews. Before 2000, positive keywords like 'actors,' 'performance,' and 'atmosphere' revealed the importance of actors' popularity and their performances, while negative keywords such as 'forced' and 'violence' pointed out narrative issues. In contrast, post-2000 cinema emphasized keywords like 'scale,' 'drama,' and 'Yang Yang,' highlighting production scale and engaging narratives as key factors. Negative keywords included 'story,' 'cheesy,' 'acting,' and 'budget,' indicating challenges in storytelling and content quality. Word2Vec analysis further highlighted differences in acting quality and emotional engagement. Pre-2000 cinema focused on 'elegance' and 'excellence' in acting, while post-2000 cinema leaned towards 'tediousness' and 'awkwardness.' In summary, this research underscores the importance of actors, storytelling, and audience empathy in Hong Kong cinema's success. The industry has evolved, with a shift from actors to production quality. These findings have implications for the broader Chinese film industry, emphasizing the need for engaging narratives and quality acting to thrive in evolving cinematic landscapes.

• Fashion & Textile Research Journal
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• v.24 no.5
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• pp.545-556
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• 2022

To overcome the pandemic, a new strategy for innovation is in demand throughout the value chains of the fashion industry that emphasize the importance of fashion technology. Accordingly, as various viewpoints and fields of debate are unfolding to consider the direction of change led by fashion technology, it is necessary to make an active value judgment precedent by understanding the differences between various opinions. This study aims to derive keywords from fashion technology used during the pandemic, to infer the characteristics of each type of perspective and to understand their characteristics. For the research, this study combines text mining analysis and content analysis. Text mining analysis is used to find statistical patterns by collecting keywords from big data from online media, and content analysis is used to interpret the data qualitatively. After analyzing the results of this study, the following observations are made. First, the perspective of positive acceptance seeks to maximize the perception and sensory action of fashion through technology; this amplifies experience, an opportunity for innovation and efficiency. Second, critical vigilance highlights the side effects of radical changes in fashion technology, characterized by concerns about capital-centered polarization, threats to human rights, and infringement of creative thinking. Lastly, the perspective of gradual adoption is the gradual convergence of technologies, characterized by the pursuit of an appropriate balance.

• Journal of Korea Technology Innovation Society
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• v.15 no.2
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• pp.369-399
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• 2012

Purpose: Health technology research & development is an important area to leading future. This study examined the current trends for 'oncogene' based on the research subject network to deduce a research front. Method: Papers were extracted from PubMed database using MeSH term for studies on 'oncogenes' and further categorized as papers published by Korean. Keywords were collected from all of articles. Research subject network was generated by keywords. Research subject network was analyzed by weighted degree centrality based social network analysis and transition of research subjects was analyzed by the time series. Results: On 'oncogenes', 'Genes, ras', 'Apoptosis', 'Signal Transduction' had a high degree centrality and currently 'Antineoplastic Agents', 'Prognosis', and 'Tumor Markers, Biological' were widely conducted. Conclusion: Consistency of research trend pattern was found by analyzing oncogene network with compromised to international vs. domestic trends. Analyzing keyword networks in various subject area, those will allow us to predict the research progress and propose evidence of research & developmental strategy.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.235-243
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• 2022

This paper aims to find promising export items for market expansion of defense export items. Germany, the UK, and France were selected as export target countries to obtain unstructured forecast data on weapons system acquisition plans for the next ten years by each country. Using the TF-IDF in text mining analysis, keywords that appeared frequently in data from three countries were derived. As a result of this paper, keywords for each country's major acquisition projects drawing. However, most of the derived keywords were related to mainstay weapon systems produced by domestic defense companies in each country. To discover promising export items from text mining, we proposed that the drawn keywords are distinguished as similar weapon systems. In addition, we assort the weapon systems that the three countries will get a plan to acquire commonly. As a result of this paper, it can be seen that the current promising export item is a weapon system related to the information system. Prioritizing overseas demands using key words can set clear market entry goals. In the case of domestic companies based on needs, it is possible to establish a specific entry strategy. Relevant organizations also can provide customized marketing support.

• Jounal of The Korea Society of Information Technology Policy & Management
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• v.11 no.6
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• pp.1503-1507
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• 2019

With the softness of online entertainment news articles and the increasing number of quick-reporting articles in the entertainment sector, many people have access to entertainment front-page articles and are now able to make reviews of celebrities. It is not easy to systematically analyze which news articles are about which celebrities in a real-time environment, although their reputation is a key factor in the entertainment agency's business strategy, which should make the most of its affiliated celebrity resources. Based on the amount of celebrity references mentioned in entertainment news data, this paper proposes an entertainment news keyword analysis system, which extracts celebrities that are the subject of the article and associates them with the celebrity entertainment agency in question. Through the system proposed in this paper, advertisers or entertainment agencies can judge the value of the celebrity as reference material for the business. In addition, it can lay the groundwork for an investment strategy by predicting the outlook for the entertainment company for brokerages and investors.

• Journal of Information Technology Applications and Management
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• v.30 no.1
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• pp.53-70
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• 2023

Artificial intelligence has become familiar with modern society, not the distant future. As artificial intelligence and machine learning developed more highly and became more complicated, it became difficult for people to grasp its structure and the basis for decision-making. It is because machine learning only shows results, not the whole processes. As artificial intelligence developed and became more common, people wanted the explanation which could provide them the trust on artificial intelligence. This study recognized the necessity and importance of explainable artificial intelligence, XAI, and examined the trends of XAI research by analyzing social networks and analyzing topics with IEEE published from 2004, when the concept of artificial intelligence was defined, to 2022. Through social network analysis, the overall pattern of nodes can be found in a large number of documents and the connection between keywords shows the meaning of the relationship structure, and topic modeling can identify more objective topics by extracting keywords from unstructured data and setting topics. Both analysis methods are suitable for trend analysis. As a result of the analysis, it was found that XAI's application is gradually expanding in various fields as well as machine learning and deep learning.