• Title/Summary/Keyword: 콘텐츠의 질

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Implementation Strategy for the Elderly Care Solution Based on Usage Log Analysis: Focusing on the Case of Hyodol Product (사용자 로그 분석에 기반한 노인 돌봄 솔루션 구축 전략: 효돌 제품의 사례를 중심으로)

  • Lee, Junsik;Yoo, In-Jin;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.25 no.3
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    • pp.117-140
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    • 2019
  • As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

Consumers Perceptions on Monosodium L-glutamate in Social Media (소셜미디어 분석을 통한 소비자들의 L-글루타민산나트륨에 대한 인식 조사)

  • Lee, Sooyeon;Lee, Wonsung;Moon, Il-Chul;Kwon, Hoonjeong
    • 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.

An Interactive Cooking Video Query Service System with Linked Data (링크드 데이터를 이용한 인터랙티브 요리 비디오 질의 서비스 시스템)

  • Park, Woo-Ri;Oh, Kyeong-Jin;Hong, Myung-Duk;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.20 no.3
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    • pp.59-76
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    • 2014
  • The revolution of smart media such as smart phone, smart TV and tablets has brought easiness for people to get contents and related information anywhere and anytime. The characteristics of the smart media have changed user behavior for watching the contents from passive attitude into active one. Video is a kind of multimedia resources and widely used to provide information effectively. People not only watch video contents, but also search for related information to specific objects appeared in the contents. However, people have to use extra views or devices to find the information because the existing video contents provide no information through the contents. Therefore, the interaction between user and media is becoming a major concern. The demand for direct interaction and instant information is much increasing. Digital media environment is no longer expected to serve as a one-way information service, which requires user to search manually on the internet finding information they need. To solve the current inconvenience, an interactive service is needed to provide the information exchange function between people and video contents, or between people themselves. Recently, many researchers have recognized the importance of the requirements for interactive services, but only few services provide interactive video within restricted functionality. Only cooking domain is chosen for an interactive cooking video query service in this research. Cooking is receiving lots of people attention continuously. By using smart media devices, user can easily watch a cooking video. One-way information nature of cooking video does not allow to interactively getting more information about the certain contents, although due to the characteristics of videos, cooking videos provide various information such as cooking scenes and explanation for each recipe step. Cooking video indeed attracts academic researches to study and solve several problems related to cooking. However, just few studies focused on interactive services in cooking video and they still not sufficient to provide the interaction with users. In this paper, an interactive cooking video query service system with linked data to provide the interaction functionalities to users. A linked recipe schema is used to handle the linked data. The linked data approach is applied to construct queries in systematic manner when user interacts with cooking videos. We add some classes, data properties, and relations to the linked recipe schema because the current version of the schema is not enough to serve user interaction. A web crawler extracts recipe information from allrecipes.com. All extracted recipe information is transformed into ontology instances by using developed instance generator. To provide a query function, hundreds of questions in cooking video web sites such as BBC food, Foodista, Fine cooking are investigated and analyzed. After the analysis of the investigated questions, we summary the questions into four categories by question generalization. For the question generalization, the questions are clustered in eleven questions. The proposed system provides an environment associating UI (User Interface) and UX (User Experience) that allow user to watch cooking videos while obtaining the necessary additional information using extra information layer. User can use the proposed interactive cooking video system at both PC and mobile environments because responsive web design is applied for the proposed system. In addition, the proposed system enables the interaction between user and video in various smart media devices by employing linked data to provide information matching with the current context. Two methods are used to evaluate the proposed system. First, through a questionnaire-based method, computer system usability is measured by comparing the proposed system with the existing web site. Second, the answer accuracy for user interaction is measured to inspect to-be-offered information. The experimental results show that the proposed system receives a favorable evaluation and provides accurate answers for user interaction.

A Study on the Continuous Utilization of Japan's Cultural Heritage Through the Cases of Silk Heritage, World Heritage, and the Japan Heritage Project in Gunma Prefecture (일본 문화유산의 연속적 활용에 관한 연구 - '군마 실크유산'과 세계유산, 일본유산 사업을 중심으로 -)

  • Lee, Chungsun
    • Korean Journal of Heritage: History & Science
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    • v.52 no.1
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    • pp.190-211
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    • 2019
  • In March 2015, The Agency for Cultural Affairs of Japan implemented a project called "Japan Heritage," which aims to promote the unique narratives of cultural properties of the region by branding the locality for revitalization in preparation for the 2020 Tokyo Olympics and Paralympics. This bottom-up approach of cultural policy has been called a "Cool Japan Strategy of Cultural Heritage" in the 21st century, which effectively incorporates local cultural heritage and tourism. However, although a total of 67 Japan Heritage projects have been designated as of December 2018, almost none has been introduced in the academic forum in Korea. On the basis of this background and a lack of academic awareness in Korea on Japan's recent cultural policies, this research aims to focus on the three cases of Gunma Prefecture implemented in local, global, and glocal aspects. To specify, the cases are the "Gunma Silk Heritage" project, implemented in 2011, the "Tomioka Silk Mill and Related Sites" project that was included on the UNESCO World Heritage List in 2014, and "The Best Wife in the World - Silk Story of Gunma," case certified as the first project of "Japan Heritage" launched in 2015. Based on the questionnaire method conducted with the World Heritage Registration Promotion Division in Gunma Prefectural Government, as well as a literature view, the research revealed that the consecutive implementation of a series of cultural heritage projects in Gunma is not coincidental, but rather a strategy aiming to create a synergism where each project complements the others. Moreover, this paper demonstrates that Gunma Prefecture has been utilizing the local silk industry as a tangible and intangible cultural resource in multi-layered heritage projects, resulting in a "spiral synergy effect" and a "chain of the recognition process." In conclusion, it illustrates the recent trend of utilizing cultural heritage in the context of the Cool Japan strategy, which seeks to move away from the administration of maintaining the status quo cultural heritage protection to a proactive one with greater potential growth. This research may thus provide meaningful insight into the utilization of domestic historical and cultural resources as well as related policy-making, in that it will ultimately promote the chain effect of linking the multiple heritage policies and projects at the local, global, and glocal levels.

The Effects of a Teacher Training Program for Elementary and Middle School Teachers: Focusing on International School for Geoscience Resources (초·중등 교원연수 프로그램의 효과 분석: 국제지질자원인재개발센터를 중심으로)

  • Lee, Yun Su;Kim, Hyoungbum
    • Journal of the Korean Society of Earth Science Education
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    • v.12 no.1
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    • pp.82-93
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    • 2019
  • The purpose of this study is to analyze the results of satisfaction for learning eco-system on the teacher training program conducted at the IS-Geo (International School for Geoscience Resources) which is KIGAM (Korea Institute of Geoscience and Mineral Resources), and to determine the satisfaction and educational effects of the teacher training programs on elementary and secondary teachers. And then, to suggest improvement points in the future operation of the teacher training program at the IS-Geo. Therefore, we conducted questionnaire of satisfaction for learning eco-system based on the data collected by a survey of 98 elementary and secondary teachers who participated in the teacher training program at the IS-Geo, from July 2017 to August 2018. The research results are as follows. First, the results of satisfaction for learning eco-system showed high values of 4.58 or higher in both the elementary and secondary programs, and the teacher training program conducted by the IS-Geo had a positive effect on the training participants. Second, internal factors indicating learning motivation and learning development were elementary teacher training 4.70 and secondary teacher training 4.64, and it is necessary to develop training contents and programs by classifying them into majors other than the earth science department. Third, intermediate factors indicating contents of education and learning curriculum were 4.67 for an elementary teacher training program and 4.72 for secondary teacher training program. In addition, in order to operate the teacher training program according to the purpose of science and technology culture, it is necessary to develop a teaching-learning model and to improve the quality of teaching. Fourth, external factors indicating learner support and quality of instructors were 4.83 for an elementary teacher training program and 4.72 for a secondary teacher training program. In particular, it is necessary to develop teaching materials that can be used immediately in school classes and can generate interest.

Clustering Method based on Genre Interest for Cold-Start Problem in Movie Recommendation (영화 추천 시스템의 초기 사용자 문제를 위한 장르 선호 기반의 클러스터링 기법)

  • You, Tithrottanak;Rosli, Ahmad Nurzid;Ha, Inay;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.57-77
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    • 2013
  • Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.