• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.773-786
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• 2017

This study was to analyze data of climate change impacts on social infrastructure using text-mining methodology, and to visualize the spatial information by integrating those with regional data layers. First of all, the study identified that the following social infrastructure; power, oil and resource management, transport and urban, environment, and water supply infrastructures, were affected by five kinds of climate factors (heat wave, cold wave, heavy rain, heavy snow, strong wind). Climate change impacts on social infrastructure were then analyzed and visualized by regions. The analysis resulted that transport and urban infrastructures among all kinds of infrastructure were highly impacted by climate change, and the most severe factors of the climate impacts on social infrastructure were heavy rain and heavy snow. In addition, it found out that social infrastructure located in Seoul and Gangwon-do region were relatively largely affected by climate change. This study has significance that atypical data in media was used to analyze climate change impacts on social infrastructure and the results were translated into spatial information data to analyze and visualize the climate change impacts by regions.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.615-625
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• 2020

The document-term frequency matrix is a term extracted from documents in which the group information exists in text mining. In this study, we generated the document-term frequency matrix for document classification according to research field. We applied the traditional term weighting function term frequency-inverse document frequency (TF-IDF) to the generated document-term frequency matrix. In addition, we applied term frequency-inverse gravity moment (TF-IGM). We also generated a document-keyword weighted matrix by extracting keywords to improve the document classification accuracy. Based on the keywords matrix extracted, we classify documents using a deep neural network. In order to find the optimal model in the deep neural network, the accuracy of document classification was verified by changing the number of hidden layers and hidden nodes. Consequently, the model with eight hidden layers showed the highest accuracy and all TF-IGM document classification accuracy (according to parameter changes) were higher than TF-IDF. In addition, the deep neural network was confirmed to have better accuracy than the support vector machine. Therefore, we propose a method to apply TF-IGM and a deep neural network in the document classification.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.1-9
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• 2020

This study aims to find new attributes by analyzing Korea and China duty free store online reviews and examine the influence of these attributes on star ratings(satisfaction)of duty free store. For study, we used Dazhong Dianping that largest online review site in China. Using R, we analyzed 5,659 reviews of Korea duty free store and 4,051 reviews of China duty free store. According to the analysis, Sale, Food and Membership attributes had a positive effect on star rating of Korea duty free store. Sale, Product, Airport, Food and Membership had a positive effect on star rating of China duty free store. This study has identified new factors such as food that showed the importance of providing space of restaurants while shopping at duty free store. This study has contributed to the existing literature by finding new attribute such as food. Practically, this finding will help to duty free industry workers better understand the impact of providing space of restaurants on duty free store.

• Archives of design research
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• v.18 no.3 s.61
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• pp.45-54
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• 2005

Visual messages are fundamental elements for performing communication and indicate the signs which are delivered from the communicator to the communicatee via channels, Generally, we can classify visual messages into two groups; linguistic factors which are rational and deliver abstract concepts and unlinguistic factors which are mental and can be expressed concretely. Especially, web site with receivers' low attention and concentration need images which can attract their attention to visual messages. That is, web site is a medium which allows us to feel visual and emotional experiences. We can call it a standard of sign systems which are consisted of various styles of digital texts. The main purpose of this study lies in that we'll analyze how homepage introductory page as one of the forms of digital text conduces a meaning action to the receivers and that we'll apprehend the structures of images and different types of signs via a semiotic approach and analyze the underlying meaning of the messages. In order to survey the structures of images we'll look into the attitude toward perceiving messages by using semantic differential method which has been developed mostly by Osgood and analyze the visual images by adopting sign types of Fuss. As the signification is created by combining signs, it is significant that we'll analyze the meaning of sings between the transmitters and receivers from the semiotic viewpoint and study the signification systems.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.118-129
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• 2018

In AI chatbot service via a messenger, a profile image of the chatbot is the first thing that users see to communicate with the chatbot. This profile image not only manages an impression about the profile owner in SNS on followers, but also makes an important impression about chatbot services on users. Thus motivated, this study investigates proper profile images tailored for the types of chatbot services and users. Specifically, I reviewed the preferred images and expressions of chatbots for each purpose of chatbot service. Then, in a case study, I collected and analyzed the representative chatbot profile images for the purpose of fun and counseling. The profile images are categorized as robot, human, animal, and abstract images. Based on these categories, I surveyed the preferred profile image of the chatbot service in either the text type or image type alternatives. For the purpose of fun, in the text version, I found that both men and women preferred a human image to others. However, in the image version, men preferred woman and robot images while women preferred cute animation character and robot images. For counseling services, both men and women preferred woman and animal images most, which is similar to the results of the text version of questionnaires as well. While both genders consistently preferred real photo images, women tend to like abstract images more than men do. I expect that the results of this study would be useful to develop the proper profile images of AI chatbot for each service purpose.

• Korean Journal of Construction Engineering and Management
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• v.20 no.3
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• pp.113-121
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• 2019

The death rate of industrial accidents per 10,000 people in Korea is two to three times higher than that of major countries. Falling accidents at the construction site happened to have caused the most deaths. Analysis of existing research and measures by national institutions showed that the industrial accident management concentrated on falling accidents was insufficient and the seasonal safety management measures were not enough. There is thus the need for research that provides detailed and enough information on falling accidents. This study, therefore, aims to overcome the limitations of existing research and safety management accident response using a methodology that provides the necessary information for the prevention of fall accidents by deriving seasonal crash characteristics of the construction site. In order to provide enough information, 387 cases of seasonal construction site falling were collected, which describes the causal relationship of accidents. Text mining using principal component analysis and cluster analysis was carried out. The analysis showed that: In the spring, snowfall and unreasonable operation of equipment including lifts were the major cause. In summer, most accidents were caused by form, insufficient safety inspection, and installation work. In autumn, weather factors such as wind and typhoon were the cause. In winter, material transportation, exterior wall work, and ignore safety precautions were the cause of the crash.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.251-256
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• 2021

This study analyzed the most frequently used navigation cases in a desktop environment. As a result of the research, GNB induces users' search as the top element of the search structure and can place color, text, icon, and image elements. LNB could be classified in the form of a dropdown, flyout, dropline and mega menu. In this study, the navigation structure of Interpark and Interpark among open markets used by users was analyzed. G-Market's GNB has a two-tier structure with color, text, image, and icon elements, and Interpark has a three-tiered horizontal label. Interpark's GNB drew attention by placing a badge on the seasonal label, which is a temporary content section, unlike G-market. It can be seen that the LNBs of both shopping malls have flyout menus that protrude when you mouse over the category menu arranged in a vertical text form under the logo placed on the left. The flyout menu has a complex structure consisting of the layout of the mega menu. This study is meaningful in revealing user experience elements by analyzing the GNB and LNB of shopping malls these days where internet shopping is increasing.

• Knowledge Management Research
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• v.22 no.2
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• pp.1-17
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• 2021

In this study, we predicted the bitcoin prices of Bithum and Coinbase, a leading exchange in Korea and USA, using ARIMA and Recurrent Neural Networks(RNNs). And we used news articles from each country to suggest a separated RNN model. The suggested model identifies the datasets based on the changing trend of prices in the training data, and then applies time series prediction technique(RNNs) to create multiple models. Then we used daily news data to create a term-based dictionary for each trend change point. We explored trend change points in the test data using the daily news keyword data of testset and term-based dictionary, and apply a matching model to produce prediction results. With this approach we obtained higher accuracy than the model which predicted price by applying just time series prediction technique. This study presents that the limitations of the time series prediction techniques could be overcome by exploring trend change points using news data and various time series prediction techniques with text mining techniques could be applied to improve the performance of the model in the further research.

• Journal of Popular Narrative
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• v.27 no.2
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• pp.179-214
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• 2021

The purpose of this study is to reconsider the background of the acceptance and formation of Manmun Manhwa in colonial Joseon. It raises questions about previous discussions that cartoons have emerged as a political product of Japan's suppression of the media. Through this, this paper look at other possibilities in consideration of the colonial Joseon's situation of inner movement and the influx of popular culture. The term "Manmun-Manhwa" was first used in 1925, not by Ahn Seok-Ju. In addition, Ahn Seok-Ju returned home after studying in Tokyo and developed a cartoon in earnest. This paper traces the background and meaning of his interest in universal comics. Ahn Seok-Ju emphasized literary characteristics and image to all cartoonists. This marked the birth of a cartoonist with literary qualities and a cartoonist with the ability to write. This represents the cultural scene of the 1920s and 1930s, which was reorganized from text-oriented to Image text, with the emergence of a unique style of universal comics. In the end, Manmun Manhwa(comics) have emerged as the purpose of modern journalism and a strategy to popularize them. Considering the circumstances of this era, the acceptance of Manmun Manhwa is being examined in various ways in the connection between comics and essays. Like this, Manmun Manhwa are an important symbol of the colonial cultural arena, reorganizing not only cartoon history but also modern media into image text.

• Journal of Popular Narrative
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• v.25 no.2
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• pp.33-69
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• 2019

This thesis aims to reveal the meanings of SF as a genre in Korea. Most of the studies on the characteristics of SF novels in Korea have revealed the meanings of characteristic elements of SF, or peripherally reviewed the characteristics of works. However, these methodologies have a limitation, such as analysis through the existing methodologies, while overlooking the identity of SF texts with the characteristics as a genre. To clearly define the value of texts in the SF genre, an understanding of the customs and codes of the genre is first needed. Thus, this thesis aims to generally handle matters like the historical context in which Korean SF was accepted by Korean society, and the meanings and characteristics when they were created and built up relationships with readers. In addition to fully investigating SF as a popular narrative & genre narrative that has not been fully handled by academic discourses, this thesis aims to practically reconsider the present/future possibilities of SF, which is currently being reconsidered given that the scientific imagination is regarded as important in the 21^st century. This thesis considers the basic signification of Korean SF texts in academic discourses. Through this work, numerous Korean SF that have not been fully handled in the area of literature and cultural phenomena will be evaluated for their significance within the academic discourses, and also reviewed through diverse research afterwards. As a result, this work will be helpful for the development of discourse and the expansion of the Korean narrative area that has been diversely changed since the 21^st century.