• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.160-169
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• 2012

'YTN Science TV' that is the only one specializing in science channel in domestic have struggled low ratings and the restricted access in spite of the performance and significance that it has contributed to the population of science. This study will seek alternatives and development challenges through the comparison with the similar channel of international for the activation of the science channel. Accordingly, this study is to review the BBC knowledge channel that have contributed the successful overseas expansion and the education for the people of its country in pursuing commercial and public interest. This study will provide significant in the activation of the science channel in domestic through review of such cases.

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.83-98
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• 1998

Who needs Media Asset Management？ ◆ Publishers ◆ Any company publishing newspapers, magazines, catalogs or web sites. ◆ Content Creators ◆ Companies who create content for use in their business ◆ Broadcasters, Advertising Agencies, Studios, Sports Houses (NBA, NFL), Corporate Training Depts, Retailers ◆ Content Distributors ◆ Cable Operators, Telecoms, Internet Service Providers, Online Service Providers Who needs Media Asset Management？ ◆ There's a LOT of money being spent on this kind of technology, and not just by 'media' companies ◆ Retailers, for catalogs, web sites, call centers ◆ Chems/Pharms, for drug. discovery, knowledge management ◆ Legal, for document and knowledge management ◆ Federal, for video surveillance and knowledge management ◆ Manufacturing, for integration of CAD, text and business-to-business applications ◆ Anyone with a Web/Content Management challenge(omitted)

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.113-124
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• 2022

News in the form of web data generates increasingly large amounts of information as unstructured text. The capability of understanding the meaning of news is limited to humans; thus, it causes information overload. This hinders the effective use of embedded knowledge in such texts. Therefore, Automatic Knowledge Extraction (AKE) has now become an integral part of Semantic web and Natural Language Processing (NLP). Although recent literature shows that AKE has progressed, the results are still behind the expectations. This study proposes a method to auto-extract surface knowledge from English news into a machine-interpretable semantic format (triple). The proposed technique was designed using the grammatical structure of the sentence, and 11 original rules were discovered. The initial experiment extracted triples from the Sri Lankan news corpus, of which 83.5% were meaningful. The experiment was extended to the British Broadcasting Corporation (BBC) news dataset to prove its generic nature. This demonstrated a higher meaningful triple extraction rate of 92.6%. These results were validated using the inter-rater agreement method, which guaranteed the high reliability.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.103-112
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• 2012

This paper is based on the perspective that the YTN Science, a science channel in Korea which plays a key role in the popularization of science, is suffering from low viewing ratings, insufficient content, and shortage of production. First, this study employs an exploratory method to identify current status of programming and operation of the Korean science channel along with its promotional strategy. Second, it aims to conduct an analysis on the science channels, specifically some major programs, of other nations including the U.S. (Discovery Channel, National Geographic Channel), United Kingdom (BBC Knowledge), Japan (Science Channel), and China (CCTV 10), seeking the possibility to apply and combine them afterward to the Korean TV channels specialized in science. A number of implications are derived from our diagnosis of present situation and analysis of abroad cases, and this helps us suggest the content development and promotional strategies as follows: First, due to the rising need for change in the programming strategy to enhance the value of the content, it is required to rearrange the programming in terms of the target audience and the viewer lifestyle, adopt a new strategy for building up the viewers' watching habit through 'stripping', and place strategic programs in prime-time. Second, as for the specific schemes of content production and application, it is recommended to establish a dual strategy in creating the content (one for conveying knowledge, the other for delivering fun), plan and use a representative character of the program, select scientific and technological topics with more Korean backgrounds, attempt strategic ties with SNS, deepen and diversify the material for programs, and implement a strategy to boost the OSMU. Finally, with regard to the promotional strategy, a constructive proposal may include raising channel awareness through science-related events and live broadcasting, performing promotional strategies by way of expanding to printed media like magazine and book publications, and intensifying online and mobile promotional strategy.

• Nutrition Research and Practice
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• v.15 no.sup1
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• pp.110-121
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• 2021

BACKGROUND/OBJECTIVES: Coronavirus disease 2019 (COVID-19) cases were first reported in December 2019, in China, and an increasing number of cases have since been detected all over the world. The purpose of this study was to collect significant news media reports on food services during the COVID-19 crisis and identify public communication and significant concerns regarding COVID-19 for suggesting future directions for the food industry and services. SUBJECTS/METHODS: News articles pertaining to food services were extracted from the home pages of major news media websites such as BBC, CNN, and Fox News between March 2020 and February 2021. The retrieved data was sorted and analyzed using Python software. RESULTS: The results of text analytics were presented in the format of the topic label and category for individual topics. The food and health category presented the effects of the COVID-19 pandemic on food and health, such as an increase in delivery services. The policy category was indicative of a change in government policy. The lifestyle change category addressed topics such as an increase in social media usage. CONCLUSIONS: This study is the first to analyze major news media (i.e., BBC, CNN, and Fox News) data related to food services in the context of the COVID-19 pandemic. Text analytics research on the food services domain revealed different categories such as food and health, policy, and lifestyle change. Therefore, this study contributes to the body of knowledge on food services research, through the use of text analytics to elicit findings from media sources.