• The Korean Fashion and Textile Research Journal
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• v.26 no.2
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• pp.198-207
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• 2024

As men's interest in grooming increases, YouTube videos teaching men about natural makeup that could help them look more presentable are becoming popular. An increasing amount of beauty content on YouTube now targets men. Therefore, this study aimed to identify the features of male-targeted beauty videos with the highest number of views and likes in order to help beauty influencers understand what subscribers want and apply effective marketing strategies. The research method set criteria for YouTuber characteristics, editing elements, and content through prior research, and analyzed through the YouTube website. The video upload date range was set from January 1, 2022 to January 1, 2024. The search keywords "male beauty YouTuber" and "male makeup" were used to find the 10 most viewed videos. The results showed that technical terms, standard words, and loanwords were generally used, and the age group was in their 30s, and the proportion of famous experts was high. The video duration of 10-15 minutes was most common, and the ratio of sound effects, background music, and subtitles was high. Makeup tips and product reviews or recommendations was the most common type of content. Especially, demonstrations of make-up application and product reviews had higher number of views. The findings of this study could provide new ideas and references to YouTubers who aspire to specialize in male beauty content, and help them produce videos that sufficiently satisfy the needs and desires of subscribers.

• The Journal of Internal Korean Medicine
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• v.45 no.3
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• pp.396-414
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• 2024

Objective: This study assessed the effectiveness of Gammaekdaejo-tang for post-stroke depression through a systematic review and meta-analysis of randomized controlled trials (RCTs). Methods: A search was conducted using keywords such as "Post-stroke Depression", "PSD", "Gammaekdaejo", and "Ganmai-dazao" on April 30, 2024. A meta-analysis was conducted according to outcome measurements, such as total effective rate (TER), HDRS (Hamilton Depression Rating Scale), and NIHSS (National Institute of Health Stroke Scale), using the Review Manager website. Results: A total of 10 RCTs was selected. The treatment group ((Gammaekdaejo-tang) or (Gammaekdaejo-tang combined with other ingredients or decoction)+Western medicine) showed significant improvement effects in terms of TER, HDRS, and NIHSS compared to the control group (Western medicine). [TER] RR: 1.19, 95% CI: 1.11 to 1.27, P<0.00001, RR: 1.24, 95% CI: 1.11 to 1.38, P<0.00001; [HDRS] MD: -2.29, 95% CI: -2.58 to -2.00, P<0.00001), MD: -3.28, 95% CI: -4.21 to -2.35, P<0.00001) [NIHSS] MD: -7.70, 95% CI: -8.52 to -6.89, P<0.00001. Conclusion: This study suggests that Gammaekdaejo-tang is effective in treating PSD. However, there are limitations, such as the small number of included studies, inability to clearly determine the effect of Gammaekdaejo-tang, inability to use various evaluation tools, and risk of bias. This research must be supplemented through systematic research design and implementation.

• Journal of Food Hygiene and Safety
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• v.31 no.3
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• pp.153-166
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• 2016

The purpose of this study was to investigate consumers' perceptions on monosodium L-glutamate (MSG) in social media. Data were collected from Naver blogs and Naver web communities (Korean representative portal web-site), and media reports including comment sections on a Yonhap news website (Korean largest news agency). The results from Naver blogs and Naver web communities showed that it was primarily mentioned MSG-use restaurant reviews, 'MSG-no added' products, its safety, and methods of reducing MSG in food. When TV shows on current affairs, newspaper, or TV news reported uses and side effects of MSG, search volume for MSG has increased in both PC and mobile search engines. Search volume has increased especially when TV shows on current affairs reported it. There are more periods with increased search volume for Mobile than PC. Also, it was mainly commented about safety of MSG, criticism of low-quality foods, abuse of MSG, and distrust of government below the news on the Yonhap news site. The label of MSG-no added products in market emphasized "MSG-free" even though it is allocated as an acceptable daily intake (ADI) not-specified by the Joint FAO/WHO Expert Committee on Food Additives (JECFA). When consumers search for MSG (monosodium L-glutamate) or purchase food on market, they might perceive that 'MSG-no added' products are better. Competent authorities, offices of education and local government provide guidelines based on no added MSG principle and these policies might affect consumers' perceptions. TV program or news program could be a powerful and effective consumer communication channel about MSG through Mobile rather than PC. Therefore media including TV should report item on monosodium L-glutamate with responsibility and information based on scientific background for consumers to get reliable information.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.247-264
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• 2016

With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.71-79
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• 2024

ChatGPT, an interactive artificial intelligence (AI) chatbot developed by Open AI in the U.S., gaining popularity with great repercussions around the world. Some academia are concerned that ChatGPT can be used by students for plagiarism, but ChatGPT is also widely used in a positive direction, such as being used to write marketing phrases or website phrases. There is also an opinion that ChatGPT could be a new future for "search," and some analysts say that the focus should be on fostering rather than excessive regulation. This study analyzed consciousness about ChatGPT for college students through a survey of their perception of ChatGPT. And, plagiarism inspection systems were prepared to establish an education support model using ChatGPT and ChatGPT. Based on this, a university education support model using ChatGPT was constructed. The education model using ChatGPT established an education model based on text, digital, and art, and then composed of detailed strategies necessary for the era of the 4th industrial revolution below it. In addition, it was configured to guide students to use ChatGPT within the permitted range by using the ChatGPT detection function provided by the plagiarism inspection system, after the instructor of the class determined the allowable range of content generated by ChatGPT according to the learning goal. By linking and utilizing ChatGPT and the plagiarism inspection system in this way, it is expected to prevent situations in which ChatGPT's excellent ability is abused in education.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.65-77
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• 2016

As respecting one's privacy becomes an important issue in mobile device data analysis, on-device analysis is getting attention, in which the data analysis is conducted inside a mobile device without sending data from the device to outside. One possible application of the on-device analysis is gender prediction using text data in mobile devices, such as text messages, search keyword, website bookmarks, and contact, which are highly private, and the limited computing power of mobile devices can be addressed by utilizing the word comparison method, where words are selected beforehand and delivered to a mobile device of a user to determine the user's gender by matching mobile text data and the selected words. Moreover, it is known that performing prediction after filtering instances using definite evidences increases accuracy and reduces computational complexity. In this regard, we propose a two-phase approach to on-device gender prediction, where both discriminability and popularity of a word are sequentially considered. The proposed method performs predictions using a few highly discriminative words for all instances and popular words for unclassified instances from the previous prediction. From the experiments conducted on real-world dataset, the proposed method outperformed the compared methods.

• The Journal of Art Theory & Practice
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• no.2
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• pp.147-168
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• 2004

This study examined the role of interpretation with various practices in art museums to seek a new meaning and a concept of art museum today. The exploration of interpretation would he a starting point to discuss about on art museums with professionals in each art-related field. While museums recognize the concept of interpretation and the scope of the functions in different levels, the study focused on the practices of collecting and exhibiting that will entrust the museum new realms of activities toward the audience. In particular, its emphases are set force on the information on the collections via the museum's web sites, interpretation policies, and theories and methodologies in exhibition development. Art museum websites well reflect how museums utilize the new medium to enhance the understanding of art works by providing in-depth art historical information, comprehensive contexts, and subject/concept based search methods. In recent decades, these have enacted changes to expand dimensions of interpretive functions in most museums, particularly in the United States and others. In an administrative perspective, Tate Gallery Interpretation Policy became an good example how an art museum put its interpretation philosophy as the basis of interpreting collection and public programs. Tate established functions of intrepretation and education not only within a task-based team but also as an intrer-divisional coorperation to provide an interpretation scheme of information provisions such as guide brochure, audio tour, multimedia content, and library. New environment and trends of museum exhibition, and its development processes stem from communication theories, object interpretation philosophy, display strategies, and various evaluation techniques through audiences, with the communication theories of Shannon and Weaver, Berlo's SMCR(Source-Message-Channel-Receiver) models were perceived as to understand the mechanism to communicate museum exhibits to visitors Suzan vogel's insight into object display strategy helped to conceive the mechanism of object recontextualization. She emphasized that the museum's practice to construe opinions and impressions through object display should be discreet and critical, therefore, the professionals to plan the exhibition should reveal the intention and their practices. For a prevailing new methodology from the field, the interpretive exhibition development processes are articulated as the front-end, formative, and summative evaluation, futhermore the team process in industrial product management models was adapted. These have turned out to be more interactive with visitors and effective to communicate the exhibition concepts and messages, hence resulting in enriched museum experiences. Finally the study concluded that understanding the aspects of interpretation should help art museums to set a framework for current practices to expand its public dimension. It can provide curators with a critical view to website planning and its content. And obviously, the interpretive exhibition development methodology will lead museum exhibition developers to be skilled in its current approaches to thematic exhibition concerning diverse subjects and topics.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.1
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• pp.277-301
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• 2020

The purpose of this study is to analyze art museum websites and derive implications for future operation of art museum websites. To this end, this research collected basic information about art museums according to '2018 National General Report of Cultural Infrastructure' and investigate the websites of 30 art museums through multi-step sampling process. This study analyzed the structure and menu of the art museum websites as well as the current state of various contents provided by the websites and the search service for the collections offered by the websites. Following sentences are the results. First of all, the art museum websites offer 5.6 top menus on average. Secondly, contents related to art museum, exhibitions, news, education, general forum, and SNS are the basic contents that should be provided on the art museum websites. Third, for contents related to news, education, and events have problems with hierarchical structure and need to be adjusted. Fourth, in the content type, specialized information contents are relatively insufficient and thus need to be improved. Fifth, the art museum websites should give sufficient information about the collection and offer directory searching hat includes keyword searching as well as detail searching service. It is also required to reorganize the directory along with the download function for searched results and the sorting service.