• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.153-167
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• 2002

With the advent of digital broadcasting, a large number of program channels become available at the user terminals such as set-top-box or PC. Channel navigation and searching become more difficult at TV terminal sides using a conventional device such as a TV remote controller. The MPEG-7 MDS (Multimedia Description Scheme) and TV Anytime set up a standard about how to describe user preferences for genre, channel, actor/actress, keyword, etc. of the TV programs, and how to describe usage history for user's program consumption behaviors and preferences. But they do not describe how to use them. In this paper, we describe an IPG (Intelligent Program Guider) system that provides TV program and channel information based on user preferences and suggest easy access to TV program that user wants. The IPG monitors user's behaviors of interacting to programs and automatically updates the user's preference changes according1y. The IPG utilizes user preferences description scheme specified in both MPEG-7 MDS and TV Anytime metadata specifications.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1163-1172
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• 2011

This study attempted to analyze between TV and family. While almost research has focused on the TV influencing family, this study has tried to contemplate family type and family communication pattern influencing TV use. Especially, this research focused on adolescent TV use. The result and conclusion are as follow: There are different children's TV watching styles based on family communication pattern(conversation-orientation and conformity-orientation). The amount of TV watching is high in conformity-orientation family pattern, and the amount of TV watching is low in conversation-orientation family pattern. In addition, conformity-orientation family pattern more prefer entertainment program, while conversation-orientation family pattern prefer informational program.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.263-271
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• 2014

Era of multi-channel digital multimedia on the Internet, cable, satellite and IPTV and the growth of new media such as terrestrial broadcast advertising with the poor rating has also dropped sharply. In this situation, terrestrial TV suggesting the introduction of in-program advertising appearing comments. In this study, the introduction of these intermediate advertising the public and professional awareness about the issue by comparing the introduction of in-program advertising feasibility was done in the purpose. Studies on terrestrial TV suggesting the introduction of in-program advertising and public opinion about the differences in perception between experts is high. The introduction of in-program advertising validity of these data for future in-program advertising to provide a basis for enforcement is expected to give.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.146-154
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• 2010

Korean TV program market has started since 1995 along with Cable TV and local TV stations and increased significantly due to Korean wave. Now the new platform such as IPTV makes a new opportunity of growth to the TV program market. This study will analyse the actual status and mechanism of Korean TV program market. To begin, Korean TV market is still dominated by terrestrial TV in domestic distribution market and in exportation even though the windows are diversified. This has influenced not only for the production market but also the distribution market as the following: continuous conflicts between terrestrial TV and independent production companies even though the significant increase of independent production in quantity ; terrestrial TV's dominance in distribution market with enormous libraries as for the major content provider. In addition, there are limited independent distributors due to the exclusive trade of TV programs by terrestrial TV. As for the exportation, foreign market for Korean TV programs are mainly Asian countries like Japan, China, etc. Furthermore, since the genre of distribution has been concentrated in dramas, it is time to make efforts to find a solution. Thus, this research can give a guideline as for the first step.

• Korean journal of communication and information
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• v.71
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• pp.194-223
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• 2015

This study explores a value chain structure of TV program including news, drama, and comedy. The purpose of this research focused on factor analysis and the relationship among viewer's program selection motivations. This research explores correlation between personal value and viewing motivation. This study was to identify the value structure of respondent on TV program(news, drama, comedy) based on means-end chain theory. The research used structured APT laddering questions and 251 data was analysed. Through such analysis, category difference by stage and relationship difference were identified and hierarchical value map was compared. There are four different value ladders: first is attributes, functional consequences, psychological consequences, and final value. The result shows that on news program the basic function is viewers are want to visual factor and quickly acquire social news and they pursue a value of personal social relationship. Whereas, on drama program, the viewers are reflected by around person, and they selected a program based on closed related person. In addition, the viewers are influenced by program's social nomination, production's brand in drama, and performer's nomination, producer and program prominence on comedy. The program selection is highly correlated on program selection's credibility, vital energetic life, and social relationship. The results shows that there was no significant difference between low involvement group and high involvement group for main category involvement group respondents.

• Journal of Korea Game Society
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• v.16 no.3
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• pp.45-54
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• 2016

This study analyzes cable TV Program "From Start to Till the End" televised by ONGAMENET from 2009 to 2015. "From Start to Till the End" is a game program that guests try to finish certain game or to complete mission once they started. Unlike other game programs, most of guests are not professional gamers thus it brings out comical challenges and enjoyments. This study examines the several components of video games played in the program. Specifically, those components are categorized according to the genre, platform, nationality, and clear time. In doing so, this study not only unpacks diverse structures of the program but also provides the blueprint of the game program.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.8
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• pp.1137-1145
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• 2000

The questionnaire survey was carried out to analyze the difference of consumers perception on apparel products presented in catalog, cable TV home shopping program, and internet shopping site. 676 men and 728 women participated in this survey and they were members of catalog shopping or cable TV home shopping companies or netizen. The results of this study show that the shoppers perception on apparel home shopping differed by the direct shopping media that they frequently utilize and by their demographic characteristics. The cable TV home shoppers had higher reliability on product quality than the shoppers using paper catalog or the internet shoppers. The cable TV home shopping members perceived that the apparel products available in cable TV home shopping were diverse and the information about the products was sufficient to decide purchase. The married women tend to think that the TV home shopping program provides diverse apparel products in the aspects of color, design, size and the information about the materials including fabric.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.47-50
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• 2015

TV는 타 도메인과 달리, 사전에 정해진 시간에 콘텐츠가 방영된다. 그러므로 TV 프로그램 추천 시스템은 시청자의 현재 시각(time-context)을 고려해야 한다. 시간 기반의 TV 프로그램 추천 방법이 다수 연구되었지만, 대부분의 기존 연구는 특정 시간대(timeslot)에서의 시청자의 선호도를 계산하는 데에만 집중되어 있고, 시청 내역 전체기간에서의 선호도를 고려하지 않은 문제점이 있다. 이러한 문제를 해결하기 위해, 시청자의 지역 선호도와 전역 선호도를 모두 고려한 시간 기반의 TV 프로그램 추천기법을 제안한다. 이를 위해 제안 방법에서는 시간대의 길이에 따라 여러 가지 선호도 모델을 사용한다. 여러 개의 선호도 모델로부터 산출된 선호도를 병합하여 가장 선호도가 높은 TV 프로그램을 추천한다. 실 데이터를 이용한 실험을 통해 기준방식과 비교함으로써, 제안 방법의 효용성을 검증하였다.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.270-283
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• 2012

With the advent of multi-channel TV, IPTV and smart TV services, excessive amounts of TV program contents become available at users' sides, which makes it very difficult for TV viewers to easily find and consume their preferred TV programs. Therefore, the service of automatic TV recommendation is an important issue for TV users for future intelligent TV services, which allows to improve access to their preferred TV contents. In this paper, we present a recommendation model based on statistical machine learning using a collaborative filtering concept by taking in account both public and personal preferences on TV program contents. For this, users' preference on TV programs is modeled as a latent topic variable using LDA (Latent Dirichlet Allocation) which is recently applied in various application domains. To apply LDA for TV recommendation appropriately, TV viewers's interested topics is regarded as latent topics in LDA, and asymmetric Dirichlet distribution is applied on the LDA which can reveal the diversity of the TV viewers' interests on topics based on the analysis of the real TV usage history data. The experimental results show that the proposed LDA based TV recommendation method yields average 66.5% with top 5 ranked TV programs in weekly recommendation, average 77.9% precision in bimonthly recommendation with top 5 ranked TV programs for the TV usage history data of similar taste user groups.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.537-542
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• 2021

Smart TVs provide a variety of services and information compared to existing TVs based on the Internet. In order to provide more personalized services or information, it is necessary to analyze users' viewing patterns and provide customized services or information based on them. The proposed system receives the user's TV viewing pattern, analyzes it, and recommends a TV program or movie as customized information to the user. For this, the system was constructed with a preprocessor and a deep learning model. The preprocessor refines the name of the TV program watched by the user, the date the TV program was watched, and the watched time. Then, the multi-attribute LSTM model trains the refined data and performs prediction.The proposed system is a system that provides customized information to users, and is believed to be a leading technology in digital convergence that combines existing IoT technology and deep learning technology.