• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.42-50
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• 2023

The development of technology has achieved digital innovation throughout the media industry, including production techniques and editing technologies, and has brought diversity in the form of consumer viewing through the OTT service and streaming era. The convergence of big data and deep learning networks automatically generated text in format such as news articles, novels, and scripts, but there were insufficient studies that reflected the author's intention and generated story with contextually smooth. In this paper, we describe the flow of pictures in the storyboard with image caption generation techniques, and the automatic generation of story-tailored scenarios through language models. Image caption using CNN and Attention Mechanism, we generate sentences describing pictures on the storyboard, and input the generated sentences into the artificial intelligence natural language processing model KoGPT-2 in order to automatically generate scenarios that meet the planning intention. Through this paper, the author's intention and story customized scenarios are created in large quantities to alleviate the pain of content creation, and artificial intelligence participates in the overall process of digital content production to activate media intelligence.

• Information Systems Review
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• v.22 no.2
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• pp.25-41
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• 2020

Along with the expectation about 5G network commercialization, interests in realistic and immersive media industries such as virtual reality (VR) are increasing. However, most of studies on VR still focus on video technologies instead of factors for popularity and consumption. Thus, the main objective of this research is to identify meaningful factors, which affect the view counts of VR videos and to provide business implications of the content strategies for VR video creators and service providers. Using a regression analysis with 700 VR videos, this study tries to find major factors that affect the view counts of VR videos. As a result, user assessment factors such as number of likes and sicknesses have a strong influence on the view counts. In addition, the result shows that both general information factors (video length and age) and content characteristic factors (series, one source multi use (OSMU), and category) are all influential factors. The findings suggest that it is necessary to support recommendation and curation based on user assessments for increasing popularity and diffusion of VR video streaming.

• Journal of Popular Narrative
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• v.25 no.4
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• pp.263-288
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• 2019

Barrier-free films enhance accessibility to audiovisual image contents by providing specific information on screen and through sound so that people with vision or hearing loss can receive the same amount of information as those without disabilities and immerse themselves in the audiovisual images. This study pays attention to barrier-free audiovisual contents in relation to the cultural civil rights of people with vision or hearing loss in South Korea. While institutional efforts have been made in the 2010s to improve the access to audiovisual media of people with vision or hearing loss, the goal of enabling people with vision or hearing loss to fully enjoy all audiovisual contents at a level equal to the non-disabled has not yet been realized. Amid the lingering conflict between disabled groups and multiplexes that has lasted years, the global video streaming service Netflix has aggressively threatened the dominance of local multiplexes with the launch of its Korean service. As Netflix, which is subject to U.S. regulations guaranteeing the rights of people with vision or hearing loss, has produced original dramas and movies involving Korean production teams, the cultural civil rights discourse of the disabled has transitioned to the issue of the rights of cultural consumers crossing national borders in the era of globalization. Changes in the media environment raise the issue of civil rights guarantees in which disabled people enjoy the right to simultaneously watch movies and comment on movies by participating in a common discourse, equally with non-disabled people. The "right to be part of the audience for Korean cinema" for Korean deaf people, which has long been neglected, should also be considered as a cultural civil right that crosses the boundaries of language, nation and disabilities. This essay examines the current issues surrounding the right to cultural entertainment of people with vision or hearing loss in South Korea in conjunction with the contemporary trend of rapid changes in the media environment and the global spread of the movement for cultural civil rights of people with disabilities, and suggests the need for visual culture studies to take a serious step toward disability studies.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.145-165
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• 2023

Recommendation system plays a significant role on relieving difficulties of selecting information among rapidly increasing amount of information caused by the development of the Internet and on efficiently displaying information that fits individual personal interest. In particular, without the help of recommendation system, E-commerce and OTT companies cannot overcome the long-tail phenomenon, a phenomenon in which only popular products are consumed, as the number of products and contents are rapidly increasing. Therefore, the research on recommendation systems is being actively conducted to overcome the phenomenon and to provide information or contents that are aligned with users' individual interests, in order to induce customers to consume various products or contents. Usually, collaborative filtering which utilizes users' historical behavioral data shows better performance than contents-based filtering which utilizes users' preferred contents. However, collaborative filtering can suffer from cold-start problem which occurs when there is lack of users' historical behavioral data. In this paper, hybrid music recommendation system, which can solve cold-start problem, is proposed based on the playlist data of Melon music streaming service that is given by Kakao Arena for music playlist continuation competition. The goal of this research is to use music tracks, that are included in the playlists, and metadata of music tracks and playlists in order to predict other music tracks when the half or whole of the tracks are masked. Therefore, two different recommendation procedures were conducted depending on the two different situations. When music tracks are included in the playlist, LightFM is used in order to utilize the music track list of the playlists and metadata of each music tracks. Then, the result of Item2Vec model, which uses vector embeddings of music tracks, tags and titles for recommendation, is combined with the result of LightFM model to create final recommendation list. When there are no music tracks available in the playlists but only playlists' tags and titles are available, recommendation was made by finding similar playlists based on playlists vectors which was made by the aggregation of FastText pre-trained embedding vectors of tags and titles of each playlists. As a result, not only cold-start problem can be resolved, but also achieved better performance than ALS, BPR and Item2Vec by using the metadata of both music tracks and playlists. In addition, it was found that the LightFM model, which uses only artist information as an item feature, shows the best performance compared to other LightFM models which use other item features of music tracks.

• The Korean Journal of Archival Studies
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• no.78
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• pp.197-249
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• 2023

This paper focus on the demand for broadcast and video archive contents by users outside broadcasters as the archive openness and sharing projects of terrestrial broadcasters have become more active in recent years. In the process of creating works using broadcasters' released video footage, the study examined the criteria by which video footage is selected and the methods and processes utilized for editing. To this end, the study analyzed the the case of the 5.18 footage video sharing project 〈May Story(Owol-Iyagi)〉 contest organized by KBS in 2022, in which KBS released its footage about the May 18 Democratic Uprising and invited external users to create new content using them. Analyzing the works that were selected as the winners of the contest, the research conducts in-depth interviews with the creators of each work. As a result, the following points are identified. Among the submitted works, many works deal with the direct or indirect experience of the May 18 Democratic Uprising and focus on the impact of this historical event on individuals and our current society. The study also examined the ways in which broadcasters' footage is used in secondary works. We found ways to use video as a means to share historical events, or to present video as evidence or metaphor. It is found that the need for broadcasters to provide a wider range of public video materials such as the May 18 Democratic Uprising, describing more metadata including copyright information before releasing selected footage, ensuring high-definition and high-fidelity videos that can be used for editing, and strengthening streaming or downloading functions for user friendliness. Through this, the study explores the future direction of broadcasters' video data openness and sharing business, and confirms that broadcasters' archival projects can be an alternative to fulfill public responsibilities such as strengthening social integration between regions, generations, and classes through moving images.