• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.510-519
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• 2019

The purpose of this study was to analyze the nutrition labeling of Guk, Tang, Jjigae HMR products to provide consumers with appropriate information when selecting products, and to provide basic data on the national policies. In this study, nutritional labels of 176 products were analyzed with 57 Guk, 75 Tang, 44 Jjigae. In the menu frequency of products, Guk has the products of the specific purposes, Tang has animal protein product, Jjigae has popular products. As a result of comparing the portion size and 9 major nutrients of the product, the average sodium content of Guk was 1558.5 mg, Tang was 1472.3mg, Jjigae was 2118.0mg. By the storage temperature, the average sodium content of HMR product was 2022.9mg in freezing(below $-18^{\circ}C$), 1676.7mg in cold($-2{\sim}10^{\circ}C$), and 1250.9mg in room temperature($1{\sim}35^{\circ}C$). Therefore, it is necessary to focus on the sodium content of Frozen products in the attempt of reducing sodium in HMR products.

• Journal of Korea Entertainment Industry Association
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• v.14 no.2
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• pp.155-164
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• 2020

This study identifies the relationship between selection value, existence value, heritage value, pride, and show on satisfaction, and suggests cultural marketing and cultural policy suggestions for Jikji cultural assets to activate Jikji as tourism cultural assets. Was intended. Therefore, the implications of this study are as follows. First, Jikji cultural property officials should develop tourism products that can mix Jikji cultural properties with the image and attractiveness of Jikji cultural properties. In addition, it is necessary to pay attention to education and public relations by city and county in providing local information, prices, and services for tourists to increase the satisfaction of tourists. Second, Jikji cultural property officials should suggest ways to create differentiating elements from tourism of other cultural properties. By emphasizing the existence, the existence value of Jikji cultural property should be increased. Third, Jikji cultural property officials should emphasize that Jikji tourism is more valuable as cultural heritage than now, and develop unique killer contents that can be boasted to others in tourism and present it to tourists. Fourth, Jikji cultural property officials should prepare a plan for local residents to recognize how excellent cultural heritage is. It should also be recognized that Jikji cultural property has high added value as a tourist factor. Lastly, Jikji cultural property officials should promote various jikji projects to local residents and tourists to increase their pride and awareness that Jikji cultural property exists in a certain area.

• Information Systems Review
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• v.22 no.3
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• pp.119-142
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• 2020

This study aims to examine the role of IT features as heuristic cues in choosing a content on YouTube. According to the heuristic-systematic model, people tend to rely on heuristic cues when they have to choose and process useful information quickly so that they could save time and reduce demands for thinking. Based on this line of reasoning, this study posits that YouTube users rely on certain IT features as heuristic cues in choosing contents before they actually watch them. Based on the prior literature and interviews with YouTube users, we develop a research model in which social endorsement, self-presentation, and interactivity are identified as potential determinants of users' attitude toward contents, which in turn influence their intention to watch them. To empirically test the research model, we conduct a laboratory experiment and a follow-up survey. The results of data analysis show that social endorsement for the content, YouTube creator's self-presentation, and interactivity have significant and positive effects on their attitude toward the content, leading to their intention to watch it. This study suggests that IT features on YouTube could be wisely utilized to increase the chance that users choose a particular content out of many competing contents when they search certain information on YouTube.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

• Archives of design research
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• v.16 no.4
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• pp.385-394
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• 2003

An investigation by KRNIC (Korea Network Information Center) on the real state of usage of internet has shown that 96.9％ of children investigated had experiences of using internet. Especially the firstly ranked item that had been answered by children as a necessity of internet was 'Studying to solve tasks' rated by 83.9％. As seen from the research result, the need as a homework sonics is actually so dominant that it cannot be ignored when considering the profitability at the area of education contents, but any profound research has not been accomplished yet. Internet has been positioned as a more effective and fruitful learning tool, and also all activities done by users for exploring informations and choosing learning items under the on-line circumstances are based on the successive mutual reactions between users and computers. Up to now much of the web based learning circumstances has been introducing the User Interface using metaphor, and the same is found dominantly from the sites for children. But in spite of the availability of metaphor mentioned above the current status is much lack of profound researches about metaphor interface; and what is more, in the case of the site for elementary school students the gap of the ability recognizing metaphor is very large between lower classes and higher classes according to the degree of mental growth but that is used to be simply ignored, then a common concept is adapted to interface for all grades of classes and moreover for infant and kindergarten without any objections. Based on foregoing problems this research has put the main focus on the groping and presenting desirable directions on the prospect design of interface for children-oriented sites by analyzing the status of practical usage of metaphor interface in the field of the sites for children-oriented learning sites with concentration upon homework supporting domains.

• Journal of Broadcast Engineering
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• v.10 no.1 s.26
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• pp.43-56
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• 2005

In the existing broadcasting environment, it is not easy to serve the bi-directional service between a broadcasting server and a TV audience. In the uni-directional broadcasting environments, almost TV programs are scheduled depending on the viewers' popular watching time, and the advertisement contents in these TV programs are mainly arranged by the popularity and the ages of the audience. The audiences make an effort to sort and select their favorite programs. However, the advertisement programs which support the TV program the audience want are not served to the appropriate audiences efficiently. This randomly provided advertisement contents can occur to the audiences' indifference and avoidance. In this paper, we propose the target advertisement service for the appropriate distribution of the advertisement contents. The proposed target advertisement service estimates the audience's profile without any issuing the private information and provides the target-advertised contents by using his/her estimated profile. For the experimental results, we used the real audiences' TV usage history such as the ages, fonder and time of the programs from AC Neilson Korea. And we show the accuracy of the proposed target advertisement service algorithm. NDS (Normalized Distance Sum) and the Vector correlation method, and implementation of our target advertisement service system.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.19-31
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• 2021

This study tried to identify the characteristics of college students' entrepreneurial intentions in the entertainment industry, focusing on existing literature studies. Based on this, it was intended to suggest realistic educational alternatives for university student start-ups and implications for start-up management to university start-up officials and those in charge of national start-up support policy. Therefore, the implications of this study are as follows. First, technology(item) for idea creation education, which is an essential element in the entertainment industry, how to connect ideas and products, technology methods that can increase content value, and user characteristics education within the entertainment industry will need to be continued. In addition, along with the idea education, it is necessary to increase the understanding of start-up business management such as financing, human resource management, marketing, and operation management, and furthermore, confidence education should be provided so that the possibility of success in an entertainment start-up and a sense of adventure in a new job can be developed. Second, the space and equipment necessary for start-up (club room, student start-up room, entertainment-related equipment, etc.) should be provided centering on the opinion survey of students who are interested in starting a business, and various regulations of universities and government for student start-up should be relaxed. will have to In addition, education for the formation of entrepreneurial knowledge inside and outside of the school, special lectures and consultations by experts, and on-the-spot education, etc., should be made to create more practical entrepreneurial knowledge. something to do. Third, for students wishing to start a business in the entertainment industry, it is necessary to inform their families about the field situation of the entertainment industry accurately so that their children can develop a positive perception rather than a negative perception when choosing a business field. In addition, by promoting various successful cases of college students to their families after starting a business, families should be encouraged so that their children can develop a challenging spirit about starting a business. Fourth, it should be possible to form continuous clubs or gatherings with friends who wish to start a business in the entertainment industry, and furthermore, an opportunity to listen to the opinions of friends who actually started a business through these meetings should be provided. In addition, the meeting and the formation of friends should create a place for discussion about writing a business plan, how to succeed in starting a business, and management of startups, and psychological stimulation activities should be conducted so that each other's will to start a business arises. Fifth, various knowledge related to start-up (methods for securing funds, management of start-up organizations, grasping information about the market in which they want to start a business, etc.) should be cultivated, and how to write a business plan for the various entertainment industry fields they want to start up. You will also need to train them to be practical. Also, based on this knowledge formation, students themselves should be able to respond to risks and changes that may occur in entrepreneurship. Lastly, it is necessary to increase the understanding of business start-up management, and various psychological stimulation activities are needed to make the confidence and fear of starting a business disappear.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.