• Proceedings of the Korea Database Society Conference
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• 2001.11a
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• pp.347-369
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• 2001

o Contents 가치 증대, 보다 편리한 Contents유통, Contents 확보 비용 절감 효과 o 수익 극대화를 위한 최적의 Contents 제공, Customized Contents 제공 o 효율적인 Contents생산 및 유통 인프라 구축 (중략)

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.515-527
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• 2006

Domestic standards for data broadcasting differ in the fact that satellite broadcasting chose MHP, cable OCAP, satellite ACAP, therefore making reuse of data contents impossible due to the differences. To resolve this problem, this study designed and implemented independent middleware class library for developing data broadcasting contents. To define class library which could bridge between applications and different middleware, standard library developing methods were used; and analysis of procedural application of each middleware was carried out. Based upon the analysis, classes with embedded transform and handle modules were defined to be linked to libraries of each middleware; and to verify the implemented class library, test contents were created to be compared to the existing contents. This kind of contents development by independent middleware class library allows for reuse of data contents easier, and develops an environment for higher quality of contents by reducing the efforts needed to learn each middleware for the developers.

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1105-1114
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• 2018

The growth rate of the domestic digital music contents market has been remarkable recently. Accordingly, the necessity of prediction for chart success of digital music contents has grown. This paper proposes prediction indexes for chart success of digital music contents through analysis of correlation between social data such as Internet news, SNS and entry rankings in Melon's weekly music charts. We collected a total of 10 social data items for each male and female artist, and executed cluster analysis. Through this, we found meaningful prediction indexes for chart success of digital music contents for each male and female artist.

• The Korean Journal of Community Living Science
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• v.27 no.spc
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• pp.665-679
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• 2016

This study examined the main factors for activating rural tourism of Jeollabuk-do using big data analysis. The tourism big data was gathered from public open data sources and social network services (SNS), and the analysis tools, 'Opinion Mining', 'Text Mining', and 'Social Network Analysis(SNA)' were used. The opinion mining and text mining analysis identified the key local contents of the 14 areas of Jeollabuk-do and the evaluations of customers on rural tourism. Social network analysis detected the relationships between their contents and determined the importance of the contents. The results of this research showed that each location in Jeollabuk-do had their specific contents attracting visitors and the number of contents affected the scale of tourists. In addition, the number of visitors might be large when their tourism contents were strongly correlated with the other contents. Hence, strong connections among their contents are a point to activate rural tourism. Social network analysis divided the contents into several clusters and derived the eigenvector centralities of the content nodes implying the importance of them in the network. Tourism was active when the nodes at high value of the eigenvector centrality were distributed evenly in every cluster; however the results were contrary when the nodes were located in a few clusters. This study suggests an action plan to extend rural tourism that develop valuable contents and connect the content clusters properly.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1154-1164
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• 2010

As an useful application in broadcasting services, the targeting service has been mainly studied to improve the service satisfaction and user usage in various media service environments based on user profile, preferences, and usage history. Targeting service is expanding its domain from broadcasting contents to interstitial contents and from fixed TV devices to mobile devices. Service data also include advertisement data, coupon, and information about media contents as well as simple broadcasting data. In this paper, the targeting data service is designed and implemented on articles, advertisement and broadcasting information on the basis of the user information. To adapt this to web-based media contents, information on user profile, preferences, and usage history is newly defined on the basis of the user metadata developed in TV-Anytime Forum and the user information defined in OpenSocial. The targeting data service is implemented to generate user preferences information and usage history pattern based on the similarity among user preference, contents information, and usage history. Based on performance evaluation, we prove that the proposed targeting data service is effectively applicable to web-based media contents as well as broadcasting service.

• Convergence Security Journal
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• v.19 no.1
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• pp.121-126
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• 2019

The big data utilization category in the sports field was mainly focused on the big data analysis to improve the competence of the athlete and the performance. Since then, 'big data technology' which collect and analyze more detailed and diverse data through the application of ICT technology such as IoT and AI has been applied. The use of big data of sports contents in future has value and possibility in the smart environment, but it is necessary to overcome the shortage and limitation of platform to manage and share sports contents. In order to solve such problems, it is important to change the perception of the companies or providers that provide sports contents and cultivate and secure professional personnel capable of providing sports contents. Also, it is necessary to implement policies to systematically manage and utilize big data poured from sports contents.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.78-84
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• 2005

Various kinds of data broadcasting services can be offered using a return-channel in digital broadcasting TV compared to analog services. In these data broadcasting environments, several data(associated with TV broadcasting programs, or not) are provided to the TV audiences except for audio/video broadcasting data. In this paper, a structure of data manager for data/object carousel, based on data broadcasting protocols, was proposed for data broadcasting services using a return-channel, and were supported to the production technologies of DTV contents. These contents application techniques for DTV will be implemented with this data manager in MPEG2-TS data broadcasts using PID(Packet ID).

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.17-24
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• 2018

This paper proposes data mining models relevant to the serial publication periods and mobile gamification likelihood of webtoon contents which were either serialized or completed in platform. The size of the cartoon industry including webtoon takes merely 1% of the total entertainment contents industry in Korea. However, the significance of webtoon business is rapidly growing because its intellectual property can be easily used as an effective OSMU (One Source Multi-Use) vehicle for multiple types of contents such as movie, drama, game, and character-related merchandising. We suggested a set of data mining classifiers that are deemed suitable to provide prediction models for serial publication periods and mobile gamification likelihood for the sake of webtoon contents. As a result, the balanced accuracies are respectively recorded as 85.0% and 59.0%, from the two models.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.82-88
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• 2017

Recently recommendation methods need personalization and diversity as well as accuracy whereas the traditional researches have been mainly focused on the accuracy of recommendation in terms of quality. The diversity of recommendation is also important to people in terms of quantity in addition to quality since people's desire for content consumption have been stronger rapidly than past. In this paper, we pay attention to similarity of data gathered simultaneously among different types of contents. With this motivation, we propose an enhanced recommendation method using correlation analysis with considering data similarity between two types of contents which are movie and music. Specifically, we regard folksonomy tags for music as correlated data of genres for movie even though they are different attributes depend on their contents. That is, we make result of new recommendation movie items through mapping music folksonomy tags to movie genres in addition to the recommendation items from the typical collaborative filtering. We evaluate effectiveness of our method by experiments with real data set. As the result of experimentation, we found that the diversity of recommendation could be extended by considering data similarity between music contents and movie contents.

• Journal of Information Technology Applications and Management
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• v.26 no.3
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• pp.121-134
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• 2019

The Fourth Industrial Revolution has differentiated technologies such as artificial intelligence, IoT(Internet of things), big data, and mobile. As the civilization develops more and more, humanity enjoy the cultural activities more than economic activity for the food and shelter. The platform structure based on the advanced information technology of the present will expand the cultural contents area in a variety of ways. Cultural contents respond sensitively to changes in consumer and will be useful experiences of human activities. Therefore, it should be noted again that the contents industry should not be limited to the discussion of the application of the fourth technology, but should be produced with emphasis on useful experiences of human being. In other words, the discussion of human activities around cultural contents should be focused on how to apply beyond the use of fourth industrial technology. Therefore, it is necessary to analyze the basis of the successful storytelling of the planning stage to connect the fourth industrial technology and human useful experience as a method for developing cultural contents, and to build and propose a model as a strategic method. This study analyzes domestic and foreign cases made by using big data among the visual contents which show continuous increase of consumption among culture industry field, and draws success factors and limit points. Next, we extract what is the successful matching factor that influenced consumer 's consciousness, and find out that the structure of culture prototype has been applied in the long history of mankind, and presents it as a storytelling model. Through the above research, this study aims to present a new interpretation and creative activity of cultural contents by presenting a storytelling model as a methodology for connecting creative knowledge, away from the general interpretation of social phenomenon applied with big data.