• Journal of the Economic Geographical Society of Korea
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• v.25 no.4
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• pp.641-656
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• 2022

This article investigates how Baedal Minjok(BaeMin) has grown to be a dominant mobility platform operator in food delivery sector in South Korea and what roles its brand and branding have played in the process, drawing on the idea of origination. For the purpose, BaeMin is considered as a typical platformized mobility service provider and origination is framed to be an appropriate analytical lens for the business sector. For the origination conception, unlike mainstream neoclassical theory and concepts, is able to deal fairly well with the issues of imperfect competition, imperfect information, and monopolistic brand rent, which are apparent in today's platformized mobility services. Drawing evidence from textual data, empirical analysis pays particular attention to discursive and symbolic dimensions of BaeMin's socio-spatial biography. It is found that national origination underpinning ethnicity comprises an important pillar of BaeMin's brand and branding. Another form of place-based origination is also observed to matter, especially in the varied relation between the mobility service brand's owner and consumers. However, this configuration of BaeMin's brand origination has yet to be fully stabilized, as it has faced with serious challenges including brand vandalism and anti-brand movement especially since its merger to German food delivery platform giant Delivery Hero in 2020. This origination crisis moment appears to be associated with a series of contractions intrinsic to so-called 'platform capitalism'.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.175-187
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• 2009

This paper shows trends in domestic and foreign web accessibility. To disclose the web accessibility observance rate, seven central adminstration institutions and another seven north-eastern cities in Gyeong gi-Do and seven major IT companies were evaluated. KADO-WAH 2.0 was used for showing the observance rate. The evaluation criteria was that of Internet Web contents accessibility Guidelines 1.0. The evaluation was limited to Guideline 1 and Guideline 2 of non-text contents and the restricted frame usage and the keyboard-only operation. The average points for three items are as follows: 65.56% for North-Eastern cities in Gyeong gi-Do and 43.71% for Central adminstration institutions and the average 29.33% for major IT companies. The observance rate was highest by 99.3% in Human-rights committee among the central administration institutions. With the observance rate of 98%, Namyang-ju city came first in Gyeong gi-Do area. Samsung electronics was the highest with 63.66% in observance rate. The Central adminstration got lowered from the average 82.14% in 2006 to the average 54.28% in 2009, with the result of 27.86% down. Accordingly, the urgent improvement for Central adminstration and Local adminstration in web accessibility is asked for. The same is true with major IT companies in web accessibility.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.51-57
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• 2023

Smart mirror is an IoT device that attaches a display and an embedded computer to the mirror and provides various information to the user along with the mirror function. This paper presents performance evaluation of the CoMirror system as an extension of the previous research in which proposed and implemented the CoMirror system that connects Smart Mirrors using a network. First, the login performance utilizing face recognition was evaluated. As result of the performance evaluation, it was concluded that the 40 face images are most suitable for face learning and only one face image is most suitable for face recognition for login. Second, as a result of evaluating the message transmission time, the average time was 0.5 seconds for text, 0.63 seconds for audio, and 2.9 seconds for images. Third, as a result of measuring a video communication performance, the average setup time for video communication was 1.8 seconds and the average video reception time was 1.9 seconds. Finally, according to the performance evaluation results, we conclude that the CoMirror system has high practicality.

• Journal of Popular Narrative
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• v.25 no.1
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• pp.87-122
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• 2019

This paper examines how the melancholia and death drive foregrounded in Kwak Ji-kyun's films have changed the affect and production trend of South Korean melodrama films of the late 1980s and thereafter. It particularly analyzes Kwak's The Home of Two Women (1987) as his exemplary melodrama film. Kwak is not only an auteur filmmaker of the 1980s and 1990s but was also a herald of South Korean New Sentimentalist films back then. The New Sentimentalist filmmakers have aspired to sophisticate the South Korean melodrama film not only by de-sentimentalizing it from the shimpa quality but also separating it from excessive emotion of shimpa that had long dominated the national cinema. This affective sophistication is directly linked to the sense of loss and melancholia/depression of the characters in the film caused by the death of one's beloved. This New Sentimentalist affect is best represented in Kwak's The Home of Two Women through its depiction of the internal conflicts of artists struggling to artistically sublimate the death drive and sense of loss. By textually analyzing The Home of Two Women, this paper not only reevaluates Kwak's film style but also reposition the topology of the New Sentimentalists in Korean film history.

• The Journal of Bigdata
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• v.7 no.2
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• pp.1-9
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• 2022

In the global era, the importance of imported food safety management is increasing. Address information of overseas food companies is key information for imported food safety management, and must be verified for prompt response and follow-up management in the event of a food risk. However, because each country's address system is different, one verification system cannot verify the addresses of all countries. Also, the purpose of address verification may be different depending on the field used. In this paper, we deal with the problem of classifying a given overseas food business address into the administrative district level of the country. This is because, in the event of harm to imported food, it is necessary to find the administrative district level from the address of the relevant company, and based on this trace the food distribution route or take measures to ban imports. However, in some countries the administrative district level name is omitted from the address, and the same place name is used repeatedly in several administrative district levels, so it is not easy to accurately classify the administrative district level from the address. In this study we propose a deep learning-based administrative district level classification model suitable for this case, and verify the actual address data of overseas food companies. Specifically, a method of training using a label powerset in a multi-label classification model is used. To verify the proposed method, the accuracy was verified for the addresses of overseas manufacturing companies in Ecuador and Vietnam registered with the Ministry of Food and Drug Safety, and the accuracy was improved by 28.1% and 13%, respectively, compared to the existing classification model.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.307-327
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• 2023

To analyze the impact of word embedding on book titles, this study utilized word embedding models (Word2vec, GloVe, fastText) to generate embedding vectors from book titles. These vectors were then used as classification features for automatic classification. The classifier utilized the k-nearest neighbors (kNN) algorithm, with the categories for automatic classification based on the DDC (Dewey Decimal Classification) main class 300 assigned by libraries to books. In the automatic classification experiment applying word embeddings to book titles, the Skip-gram architectures of Word2vec and fastText showed better results in the automatic classification performance of the kNN classifier compared to the TF-IDF features. In the optimization of various hyperparameters across the three models, the Skip-gram architecture of the fastText model demonstrated overall good performance. Specifically, better performance was observed when using hierarchical softmax and larger embedding dimensions as hyperparameters in this model. From a performance perspective, fastText can generate embeddings for substrings or subwords using the n-gram method, which has been shown to increase recall. The Skip-gram architecture of the Word2vec model generally showed good performance at low dimensions(size 300) and with small sizes of negative sampling (3 or 5).

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.769-778
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• 2023

This study compared and analyzed parental leave and child allowance, two major policies among solutions to the current serious low fertility rate problem, using unstructured data, and sought future directions and implications for related response policies based on this. The collection keywords were "low fertility + parental leave" and "low fertility + child allowance", and data analysis was conducted in the following order: text frequency analysis, centrality analysis, network visualization, and CONCOR analysis. As a result of the analysis, first, parental leave was found to be a realistic and practical policy in response to low fertility rates, as data analysis showed more diverse and systematic discussions than child allowance. Second, in terms of child allowance, data analysis showed that there was a high level of information and interest in the cash grant benefit system, including child allowance, but there were no other unique features or active discussions. As a future improvement plan, both policies need to utilize the existing system. First, parental leave requires improvement in the working environment and blind spots in order to expand the system, and second, child allowance requires a change in the form of payment that deviates from the uniform and biased system. should be sought, and it was proposed to expand the target age.

• The Transactions of the Korea Information Processing Society
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• v.13 no.5
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• pp.209-216
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• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• Informatization Policy
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• v.31 no.1
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• pp.3-31
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• 2024

This study aimed to examine public concerns in South Korea considering the country's unique context, triggered by the advent of generative artificial intelligence such as ChatGPT. To achieve this, comments from 102 YouTube video news related to ethical issues were collected using a Python scraper, and morphological analysis and preprocessing were carried out using Textom on 15,735 comments. These comments were then analyzed using a Correlated Topic Model (CTM). The analysis identified six primary topics within the comments: "Legal and Ethical Considerations"; "Intellectual Property and Technology"; "Technological Advancement and the Future of Humanity"; "Potential of AI in Information Processing"; "Emotional Intelligence and Ethical Regulations in AI"; and "Human Imitation."Structuring these topics based on a correlation coefficient value of over 10% revealed 3 main categories: "Legal and Ethical Considerations"; "Issues Related to Data Generation by ChatGPT (Intellectual Property and Technology, Potential of AI in Information Processing, and Human Imitation)"; and "Fear for the Future of Humanity (Technological Advancement and the Future of Humanity, Emotional Intelligence, and Ethical Regulations in AI)."The study confirmed the coexistence of various concerns along with the growing interest in generative AI like ChatGPT, including worries specific to the historical and social context of South Korea. These findings suggest the need for national-level efforts to ensure data fairness.

• Journal of the Daesoon Academy of Sciences
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• v.50
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• pp.33-68
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• 2024

Byun Chan-rin (1934-1985) intertextually reconciled important world religions such as Christianity, Buddhism, Taoism, and Confucianism from the perspective of Pungryu (風流), also known as Seon (僊), which he considered to be the foundation of the Korean spirit. Naturally, his category of Pungryu also encompassed modern Korean national religions. He emphasized the necessity of a neo-religion in order to overcome the exclusive limitations of various world religions as each was bound by their own tradition, and hence deviated from the mainstream of the Great Way of Pungryu. He also appreciated various indigenous new religions in modern Korea, including concept of epoch-making and the practices of Kang Il-sun (姜一淳), as "neo-religion" that could overcome the limitations of world religions by elevating the magical activities of shamanism to the Great Way. His appraisal was positive, and he refrained from dismissing this growing movement as "superstitions" or "new emerging religions" embraced by the common people. From his viewpoint, the important indigenous new religions in modern Korea were not the ruling religions of the empire but alternative religions of the colonial people, and the concept of "Great Opening of the Later World (後天開闢)" in modern indigenous Korean religions and Kang's idea of the Resolution of Grievances for Mutual Beneficence (解冤相生) were creative evolutions of religion that overcame the contradictions and limitations of the world's religions. He presented the insight of a spiritual seeker who heralded the era of "SBNR" (spiritual but not religious), which seeks new possibilities for spirituality by escaping limitations of religiosity.