• Journal of the Korea Society of Computer and Information
• /
• v.28 no.10
• /
• pp.85-92
• /
• 2023

In this paper, we propose a method for automatically generating story-based abbreviated summaries from long-form dramas and movies. From the shooting stage, the basic premise was to compose a frame with illusion of depth considering the golden division as well as focus on the object of interest to focus the viewer's attention in terms of content delivery. To consider how to extract the appropriate frames for this purpose, we utilized elemental techniques that have been utilized in previous work on scene and shot detection, as well as work on identifying focus-related blur. After converting the videos shared on YouTube to frame-by-frame, we divided them into a entire frame and three partial regions for feature extraction, and calculated the results of applying Laplacian operator and FFT to each region to choose the FFT with relative consistency and robustness. By comparing the calculated values for the entire frame with the calculated values for the three regions, the target frames were selected based on the condition that relatively sharp regions could be identified. Based on the selected results, the final frames were extracted by combining the results of an offline change point detection method to ensure the continuity of the frames within the shot, and an edit decision list was constructed to produce an abbreviated summary of 62.77% of the footage with F1-Score of 75.9%

• Korean Journal of Culture and Social Issue
• /
• v.9 no.2
• /
• pp.19-39
• /
• 2003

The purpose of this study was to investigate the degree of link with internet media and a internet addiction disposition of adolescents. The subjects were 500 students attending to middle and high schools consisted of male and female. The instruments were "the questionnaire on the present conditions of internet use" consisted of 14 items(Cronbach's α=.71) and "the internet addiction rating scale" consisted of 20 items(Cronbach's α=.73). These questionnaire were revised by this researcher. For data analysis, chisqure and ANOVA were used. The main results were as follows. First, a boy students and the vocational high school and the middle school each have more negative response than a girl students and the humanistic high schools in the present conditions of internet use and the judgement on a harmful object of internet space. Second, a boy students have higher than a girl students in an internet addiction disposition. Third, an internet addiction related with the times link with internet, the type of internet game, and the content of internet space(a lustful and violent objects). The various methods for the prevent with the internet addiction of adolescents discussed with based on the previous studies.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.5
• /
• pp.183-189
• /
• 2023

This paper proposes a new JPEG format, All-in-JPEG, which can include not only multiple photos but also various media such as audio and text by extending the JPEG format. All-in-JPEG add images, audio, and text at the existing JPEG file, and stores meta information by utilizing the APP3 segment of JPEG. With All-in-JPEG, smartphone users can save many pictures taken in burst shots in one file, and it is also very convenient to share them with others. In addition, you can create a live photo, such as saving a short audio at the time of taking a photo or moving a part of the photo. In addition, it can be used for various applications such as a photo diary app that stores images, voices, and diary text in a single All-in-JPEG file. In this paper, we developed an app that creates and edits All-in-JPEG, a photo diary app, and a magic photo function, and verified feasibility of the All-in-JPEG through them.

• Information Systems Review
• /
• v.24 no.1
• /
• pp.59-87
• /
• 2022

Since over-the-top (OTT) service has emerged as a new way of consuming video contents, OTT markets grow exponentially and the competition among the OTT services becomes intense. Only limited systematic research effort has been paid to understand why users subscribe such OTT services among other services. Therefore, we used developmental sequential mixed methods approach to find out the quality factors and their effect on post-subscription experiences and continuance intention. In the qualitative study, we derived six factors which a user considers important to continue the subscription. Based on the explored factors, we hypothesized a research model with modified three qualities from ISSM. The proposed research model was validated through quantitative research, a survey of 226 OTT service users in South Korea, using structural equation modeling. The results indicated that content quality is the key factor affecting both perceived enjoyment and satisfaction whereas system quality affects satisfaction, and service quality only affects enjoyment. Enjoyment affects satisfaction which sequentially affects continuance usage intention. This study contributes to research by modifying ISSM through mixed methods. It also provides OTT service providers with insight to enhance users' post experience and continuance intention to use the service through qualities derived from the interview.

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

• Journal of the Korean Institute of Landscape Architecture
• /
• v.52 no.3
• /
• pp.89-102
• /
• 2024

This study aims to examine the characteristics of the user experience of New Town neighborhood parks and explore issues that diversify the experience of the parks. In order to quantitatively analyze a large amount of park visitors' experiences, text-based Naver blog reviews were collected and analyzed. Among the Phase 1 and 2 New Towns, the parks with the highest user experience postings were selected for each city as the target of analysis. Blog text data was collected from May 20, 2003, to May 31, 2022, and analysis was conducted targeting Ilsan Lake Park, Bundang Yuldong Park, Gwanggyo Lake Park, and Dongtan Lake Park. The findings revealed that all four parks were used for everyday relaxation and recreation. Second, the analysis underscores park's diverse user groups. Third, the programs for parks nearby were also related to park usage. Fourth, the words within the top 20 rankings represented distinctive park elements or content/programs specific to each park. Lastly, the results of the network analysis delineated four overarching types of park users and the networks of four park user types appeared differently depending on the park. This study provides two implications. First, in addition to the naturalistic characteristics, the differentiation of each park's unique facilities and programs greatly improves public awareness and enriches the individual park experience. Second, if analysis of the context surrounding the park based on spatial information is performed in addition to text analysis, the accuracy of interpretation of text data analysis results could be improved. The results of this study can be used in the planning and designing of parks and greenspaces in the Phase 3 New Towns currently in progress.

• Journal of Korean Library and Information Science Society
• /
• v.54 no.4
• /
• pp.359-392
• /
• 2023

Digital citizenship includes an evolving set of knowledge and skills related to effectively and ethically using technology, especially when interacting with other people, information, and media in the online context. As public libraries have long provided access to and training with a variety of technologies, this study explores how digital citizenship has been covered in public library programming to identify potential trends and best practices. A purposive sampling of public library recipients of the American Library Association (ALA) and Information Today Inc.'s Library of the Future Award over the past 11 years (2013-2023) identified 7 case libraries to review. The titles and descriptions of 337 relevant library programs for audiences of school-aged children (5 years old and up) to seniors were collected for a 2-month period from each library's website and analyzed using Ribble & Parks (2019) 9 elements of digital citizenship. The findings suggest that programming related to digital citizenship most often addresses themes connected to digital access and digital fluency through coverage of topics related to computer and technology use. Based on themes and examples from the findings, public libraries are encouraged to expand upon existing programs to integrate all elements of digital citizenship, strive for inclusive and accessible digital citizenship education for all ages, and leverage resources and expertise from relevant stakeholders and community partnerships.

• Journal of Science Education
• /
• v.47 no.3
• /
• pp.251-262
• /
• 2023

In this study, we examine other factors that may contribute to the decline in students' academic performance and educational attainment. Many media reports, as well as previous studies, have suggested that virtual learning is the main reason for the decline in students' academic performance. However, the 2020 National Student Achievement Survey, which was conducted in conjunction with the COVID-19 Distance Learning Environment Student Survey, showed that students were highly satisfied with distance learning (70-80%), and the analysis of the National Assessment of Educational Achievement showed that students' academic performance had already been declining year by year since 2017, with a general downward curve. For further confirmation, we analyzed the performance of high school students on mock exams and found that their performance was not normally distributed, but rather a right-skewed U-shaped distribution with a shrinking number of medians and severe polarization. We found that this phenomenon is not simply because of the mode or quality of the virtual classroom, but to a variety of factors, including environmental influences such as care and management at home, changes in investment in private education, increased time spent on online devices while taking virtual classes at the bottom, and increased time spent watching online content, games, and videos that are not related to learning.

• Journal of the Korean Society for information Management
• /
• v.41 no.1
• /
• pp.261-282
• /
• 2024

This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.3
• /
• pp.97-109
• /
• 2024

In the field of domestic tourism, tourism trend analysis of tourism consumers, both international tourists and domestic tourists, is essential not only for the Korean tourism market but also for local and governmental tourism policy makers. e will explore the keywords and sentiment analysis on social media to establish a marketing strategy plan and revitalize the domestic tourism industry through communication and information from tourism consumers. This study utilized TEXTOM 6.0 to analyze recent trends in Korean tourism. Data was collected from September 31, 2022, to August 31, 2023, using 'Korean tourism' and 'domestic tourism' as keywords, targeting blogs, cafes, and news provided by Naver, Daum, and Google. Through text mining, 100 key words and TF-IDF were extracted in order of frequency, and then CONCOR analysis and sentiment analysis were conducted. For Korean tourism keywords, words related to tourist destinations, travel companions and behaviors, tourism motivations and experiences, accommodation types, tourist information, and emotional connections ranked high. The results of the CONCOR analysis were categorized into five clusters related to tourist destinations, tourist information, tourist activities/experiences, tourism motivation/content, and inbound related. Finally, the sentiment analysis showed a high level of positive documents and vocabulary. This study analyzes the rapidly changing trends of Korean tourism through text mining on Korean tourism and is expected to provide meaningful data to promote domestic tourism not only for Koreans but also for foreigners visiting Korea.