• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.21-33
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• 2022

Recently, the recommender system has been widely used in various fields such as movies, music, online shopping, and social media, and in the meantime, the recommender model has been developed from correlation analysis through the Apriori model, which can be said to be the first-generation model in the recommender system field. In 2005, many models have been proposed, including deep learning-based models, which are receiving a lot of attention within the recommender model. The recommender model can be classified into a collaborative filtering method, a content-based method, and a hybrid method that uses these two methods integrally. However, these basic methods are gradually losing their status as methodologies in the field as they fail to adapt to internal and external changing factors such as the rapidly changing user-item interaction and the development of big data. On the other hand, the importance of deep learning methodologies in recommender systems is increasing because of its advantages such as nonlinear transformation, representation learning, sequence modeling, and flexibility. In this paper, among deep learning methodologies, RNN, CNN, and GAN-based models suitable for sequential modeling that can accurately and flexibly analyze user-item interactions are classified, compared, and analyzed.

• Journal of Advanced Navigation Technology
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• v.27 no.3
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• pp.306-313
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• 2023

Realistic and graphics-based virtual reality content is based on 360-degree videos, and viewport extraction through the viewer's intention or automatic recommendation function is essential. This paper designs a viewport extraction system based on multiple object tracking in 360-degree videos and proposes a parallel computing structure necessary for multiple viewport extraction. The viewport extraction process in 360-degree videos is parallelized by composing pixel-wise threads, through 3D spherical surface coordinate transformation from ERP coordinates and 2D coordinate transformation of 3D spherical surface coordinates within the viewport. The proposed structure evaluated the computation time for up to 30 viewport extraction processes in aerial 360-degree video sequences and confirmed up to 5240 times acceleration compared to the CPU-based computation time proportional to the number of viewports. When using high-speed I/O or memory buffers that can reduce ERP frame I/O time, viewport extraction time can be further accelerated by 7.82 times. The proposed parallelized viewport extraction structure can be applied to simultaneous multi-access services for 360-degree videos or virtual reality contents and video summarization services for individual users.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.195-204
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• 2023

In this study, prompt engineering that improves prompts was explored to improve the performance of teaching and learning materials recommendations using generative artificial intelligence such as GPT and Stable Diffusion. Picture materials were used as the types of teaching and learning materials. To explore the impact of the prompt composition, a Zero-Shot prompt, a prompt containing learning target grade information, a prompt containing learning goals, and a prompt containing both learning target grades and learning goals were designed to collect responses. The collected responses were embedded using Sentence Transformers, dimensionalized to t-SNE, and visualized, and then the relationship between prompts and responses was explored. In addition, each response was clustered using the k-means clustering algorithm, then the adjacent value of the widest cluster was selected as a representative value, imaged using Stable Diffusion, and evaluated by 30 elementary school teachers according to the criteria for evaluating teaching and learning materials. Thirty teachers judged that three of the four picture materials recommended were of educational value, and two of them could be used for actual classes. The prompt that recommended the most valuable picture material appeared as a prompt containing both the target grade and the learning goal.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.185-205
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• 2023

As the tourism industry recovers post the COVID-19 pandemic, an increasing number of tourists are utilizing various platforms to leave reviews. However, amidst the vast amount of data, finding useful information remains challenging, often leading to time and cost inefficiencies in selecting travel destinations. Despite ongoing research, there are limitations due to the absence of ratings or the presence of different rating formats across platforms. Moreover, inconsistencies between ratings and the content of reviews pose challenges in developing recommendation models. To address these issues, this study utilized 7,104 reviews of tourist spots in Jeju Island to develop a specialized satisfaction index for Jeju tourist attractions and employed this index to construct a 'Rating Prediction Model.' To validate the model's performance, we predicted the ratings of 700 experimental data points using both the developed model and an LSTM approach. The proposed model demonstrated superior performance with a weighted accuracy of 73.87%, which is approximately 4.67% higher than that of the LSTM. The results of this study are expected to resolve the discrepancies between ratings and review contents, standardize ratings in reviews without ratings or in various formats, and provide reliable rating indicators applicable across all areas of travel in different domains.

• 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.

• Information Systems Review
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• v.24 no.1
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• pp.1-19
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• 2022

Social media-based communication has become crucial part of our personal and official lives. Therefore, it is no surprise that social media sentiment analysis has emerged an important way of detecting potential customers' sentiment trends for all kinds of companies. However, social media sentiment analysis suffers from huge number of sentiment features obtained in the process of conducting the sentiment analysis. In this sense, this study proposes a novel method by using Bayesian Network. In this model MBFS (Markov Blanket-based Feature Selection) is used to reduce the number of sentiment features. To show the validity of our proposed model, we utilized online review data from Yelp, a famous social media about restaurant, bars, beauty salons evaluation and recommendation. We used a number of benchmarking feature selection methods like correlation-based feature selection, information gain, and gain ratio. A number of machine learning classifiers were also used for our validation tasks, like TAN, NBN, Sons & Spouses BN (Bayesian Network), Augmented Markov Blanket. Furthermore, we conducted Bayesian Network-based what-if analysis to see how the knowledge map between target node and related explanatory nodes could yield meaningful glimpse into what is going on in sentiments underlying the target dataset.

• Information Systems Review
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• v.20 no.1
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• pp.1-16
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• 2018

The development and generalization of the Internet increased the popularity of food delivery service applications in Korea. The food delivery market based on online-to-offline service is growing rapidly. This study compares the usability of Korean food delivery service application between that of Chinese food delivery service application. This study suggests improvement points for Korean food delivery service applications. To conduct this study, we explore the status of various food delivery service applications and conduct interviews and surveys based on the honeycomb model developed by Peter Morville. This study obtained the following results. First, all restaurants participating in the Korean food delivery service must be able to accept order through the application. Second, the shopping cart function must be able to accept order of all restaurants simultaneously. Third, when users look for menu recommendation, their purchase history and shopping cart functions should appear at the first page of the website. Users should be able to perceive the improved usability of the website using those functions. Fourth, when the search window is fixed on the top of each page, users should be able to find the information they need. Fifth, the application must allow users to find the exact location of the delivery person and the estimated delivery time. Finally, the restaurants'address should be disclosed and fast delivery time should be confirmed to enhance users'trust on the application. This study contributes to academia and industry by suggesting useful insight into food delivery service applications and improving the point of food delivery service application in Korea.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.743-751
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• 2017

As smart phones are becoming popular, an operating system is being used at wearable devices, home appliances and smart TVs. A user is able to use various applications on devices with operating system, but there is an increased threat of hacker. Thus, the technology for detecting the forgery of applications is becoming more important on operating system. To detect the forgery of the application, a digital signature technology is used on the filed of application digital signature. According to W3C recommendation, the signing process of application digital signature must be performed at least twice, and the applications which are signed by the application digital signature have to be validated for all signature files when the application is installed in the operating system. Hence, the performance of the application digital signature validation system is closely related to the installer performance on the operating system. Existing validation system has performance degradation due to redundancy of integrity verification among application components. This research was conducted to improve the performance of the application digital signature validation system. The proposal of validation system which is applied proxy system shows a performance improvement compared to the existing verification system.

• Korean Journal of Digital Imaging in Medicine
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• v.12 no.1
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• pp.33-41
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• 2010

National Cancer Screening Project and Korean Society of Breast Imaging recommend that breast cancer screening should be performed on those aged 40 and above. Nevertheless, this recommendation is usually ignored by a number of medical institutions. The purpose of this study is to emphasize the necessity of an age limitation in screening mammography. Ten institutions were randomly selected and telephone inquiries about patients' age limitation and internal guidelines were set up. The 3,214 women, who underwent screening mammography through 'GE Senography 2000D' in each hospital, were classified into five groups according to age(from 20s to 40s, at intervals of 5). And then, collected data was analyzed by a radiologist in accordance with ACR-BIRADS(American College of Radiology Breast Imaging Reporting and Data System), through which breast parenchymal density and the results of analysis were categorized in order to predict the sensitivity of mammography. Information about craniocaudal-view mammograms was automatically produced by use of GE Senography 2000D, and the average glandular dose was retrospectively analyzed through the program 'Excel 2007.' Two institutions did not set the age limitation. Other seven institutions internally allowed those who wanted to receive mammography regardless of age. Approximately 99% of those aged 20 to 29 were judged as having the dense breast. In those aged 35 to 39, breast parenchymal density tended to be lower, but the fatty breast to increase. In the case of 'category-zero' that does not need additional tests, the rate of 'heterogeneously dense' and 'extremely dense' reached to 83.1% and 15.1% respectively. Regarding dense breasts, there was no sufficient information for image reading. The glandular dose, applied to 3,214, was 1.47mGy on the average. In those aged 20 to 24 who are sensitive to radiation, the average glandular dose indicated 1.59mGy. Those aged 35 and above showed the lowest value, 1.43mGy. In those aged 35 to 39, the breast tended to change from denseness to fattiness. The average glandular dose was lowest in those aged 35 and above, which suggests that screening mammography should be periodically performed on those aged 35 and above in order that breast cancer may be early detected. On the other hand, in those aged less than 35, it is difficult to analyze mammograms due to the high density of breast parenchyma, and also retakes become frequent. In particular, subjects may be exposed to excessive doses. Accordingly, it should be substituted by breast self-examination or clinical breast examination. In case of need, it is advisable to perform ultrasonography.

• Journal of the Korean Society of Food Culture
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• v.16 no.2
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• pp.147-157
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• 2001

In order to investigate the eating out behavior of university students, this survey was conducted using the questionaires for 710 students(369 male, 341 female) from 11 universities in Seoul. It was revealed that 39.4% of the subjects spent $60,000{\sim}100,000$ won for monthly eating out cost and 57.8% of them ate out more than once a day. Most of them expended less than 3,500 won for lunch, while 36.5% of them spent $4,000 {\sim}5,000$ won for dinner. Dinner was regarded more important than lunch. Korean foods were the most preferred menu for eating out with friends and fast foods were the second. But Boonsik(snack bar foods), Chinese foods and Japanease foods were rarely selected. Frequency of selecting fast foods was 8 times greater than that of Boonsik. This indicates that the preference of western flavor and the pursuit of convenience is getting more obvious. While dating, western foods were preferred, followed by Korean foods, fast foods. The 80 kinds of foods were reported as favored eating out foods. Although 50 among 80 were Korean foods, the rest of them were Koreanized foreign foods most of those were western style. This may suggest that when the students become adults, they will be much fond of western dish for their dinning out. This tendency of preferring western flavor were much apparent in foods for dinner compared with lunch. In both sexes, the standard of food choice was in the order of taste, price, mood, hygiene, service and brand name. But male students were more conscious of price and service while female students were more concerned about taste and hygiene. Most unsatisfying feature in restaurant was unstable atmosphere for both sexes. Taste was the most important sensory factor in selecting the foods, followed by appearance, smell and texture. Major source of restaurant information was recommendation by friends or relatives. But the use of internet or magazine was negligible. Female students had more positive attitude, compared with male students, in using restaurant information and pursuing eating out for gourmet. The dining out menu of which price ranges about $3,000{\sim}5,000$ won could be preferable foods for most people. Therefore, instead of blaming them for eating too much fast foods, new menus which fit the food preference and affordability of the students should be developed.