• Journal of Korea Multimedia Society
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• v.10 no.1
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• pp.128-138
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• 2007

With the development of broadcasting technology from analogue to interactive digital, the number of TV channels and contents provided to audience is increasing in a rapid speed. In this multi-media and multi-channel world, it is difficult to adapt to the increase of TV channel numbers and their contents merely using remote controller to search channels. Due to this reason, EPG (Electronic Program Guide) has been one of the essential services providing convenience to audience. So EPG complying with European DVB-MHP specifications, which will be also our domestic standard, is proposed in this paper. In order to provide audiences with DiTV contents they preferred, we apply collaborative filtering algorithm to recommend contents according to preference value of audience group with similar preference. And we use JavaXlet application which is based on MHP to implement this EPG, while the result can be verified by OpenMHP emulator.

• 한국HCI학회:학술대회논문집
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• 2006.02b
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• pp.416-423
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• 2006

본 논문은 개인별 프로그램 선호도와 채널 선호도를 기반으로 프로그램을 추천해주는 선호프로그램편성표를 구성하여 이를 효과적으로 보여주는 사용자인터페이스(UI) 모델을 제안한다. 현재 개인 맞춤화 전자프로그램가이드(PEPG)에 대한 다양한 연구가 이루어지고 있으나 주로 추천 알고리즘 연구에 그 초점이 맞춰져 있는 실정이다. 동일한 추천 알고리즘에 의해 추출된 프로그램이라 할지라도 정렬 순서와 디스플레이 방법에 따라 편성표를 이용하는 사용자의 용이성이 달라질 수 있다. 이에 본 논문은 추천 알고리즘에 의해 추출된 프로그램들의 선호도에 현재시간 기준으로 가중치를 부과하여 그 프로그램들의 선호도를 합산한 값으로 정렬한 편성표를 구성하였다. 이러한 선호프로그램편성표는 시청자가 가장 선호하는 프로그램과 채널이 최우선으로 보여지게 되므로 쉽고 빠르게 원하는 프로그램을 찾아갈 수 있다는 장점이 있다. 따라서, 사용자는 원하는 프로그램이 시작할 때까지 기다리거나 하는 시간의 낭비없이 시청이 가능하다. 본 논문을 통해 향후 등장하게 될 많은 개인 맞춤화된 서비스들을 개발하는데 도움이 될 수 있길 바란다.

• Convergence Security Journal
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• v.23 no.3
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• pp.57-64
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• 2023

Due to the COVID-19 pandemic, the broadcasting industry has been greatly affected, to the extent that the footprint of travel programs has disappeared. Although travel programs have been back on the air since 2022, there remains a task of recovering the stagnant desire for travel. Based on a study that travel programs have a positive impact on viewers' travel intentions, this study examined a data service that provides preferred additional information on travel programs, considering the broadcasting environment of satellite broadcasters that transmit multiple travel programs through various channels. Specifically, preferred additional information was investigated for travel programs of various genres and formats, and a feature model based on FODA was designed to be used when the satellite broadcaster decides the data service configuration. In addition, the necessary information for operating the data service was defined based on the feature model, and a method of transmitting it using the DVB-S SI, a domestic satellite broadcasting standard, was devised. The feasibility of this study was also confirmed using a DVB-MHP based data service prototype.

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2008.11a
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• pp.145-148
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• 2008

방송에서의 광고의 비중이 높아짐에 따라 광고 수익을 극대화하기 위한 기술의 발전이 활발히 이루어지고 있다. 최근의 이러한 광고 관련 기술들을 일반적으로 Advanced Advertising 이라고 하며 그 중 시청자의 선호에 맞는 광고만을 시청자에게 제공하는 타깃광고(Targeted Advertising) 방식 등 수신기별로 특화된 광고를 제공하는 기술을 클라이언트 기반 광고 삽입 방식이라고 한다. 북미의 인터랙티브 케이블방송 규격인 OCAP(OpenCable Application Platform)은 OCAP DPI(Digital Program Insertion) 라는 명칭의 클라이언트 기반 광고 삽입 방식에 대한 북미 일부 지역에서의 시험 방송의 성공한 후 관련 규격을 OCAP1.1-I01 에 발표하기에 이르렀다. 조만간 상용화되면 OCAP DPI 를 통해 북미 케이블방송 사업자들의 광고 수익 향상에 기여할 것은 물론이고 시청자들의 만족도를 향상시킬 것이다. 이런 움직임은 케이블 진영뿐만 아니라 Open IPTV Forum, ATSC 등 IPTV 나 지상파 TV 진영에서도 이 기술에 대한 타당성 검증 및 표준화가 논의가 활발히 진행되고 있는 실정이다. 본 논문은 클라이언트 기반 광고 삽입 기술에 대해 OCAP DPI 를 구현한 경험을 바탕으로 그 원리 및 동작을 설명하고, DVR(Digital Video Recorder) 또는 PVR(Personal Video Recorder)의 주요 기능인 스토리지에 방송스트림을 저장하고 재생하는 기능을 이용하는 광고 삽입 방법에 대해 제안하며, Cable-IPTV Hybrid 의 웹 접근성을 이용하여 웹 서버에 저장되어 관리 및 운용되는 광고컨텐츠의 스트리밍을 통한 광고 삽입 방법에 대한 제안하고, 마지막으로 실제 이러한 광고 삽입 기술을 적용하는 데에 있어 발생되는 문제점들을 언급하고 그 해결에 대한 의견을 제시한다.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.567-571
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• 2009

Sports game broadcasting system uses multiple video cameras in order to offer exciting and dynamic scenes for the TV audiences. Since, however, the traditional broadcasting system edits the multiple views into a static video stream, it is difficult to provide the intelligent broadcasting service that summarizes or retrieves specific scenes or events based on the user preference. In this paper, we propose the summarization and retrieval system for the soccer videos based on multiple cameras. It extracts the highlights such as shot on goal, crossing, foul, and set piece using dynamic Bayesian network based on soccer players' primitive behaviors annotated on videos, and selects a proper view for each highlight according to its type. The proposed system, therefore, offers users the highlight summarization or preferred view selection, and can provide personalized broadcasting services by considering the user's preference.

• Smart Media Journal
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• v.13 no.2
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• pp.62-67
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• 2024

Due to technological advancements in viewing devices and the COVID-19 pandemic, a lot of OTT-only content is being produced and distributed as people shift from traditional movie theater viewing and broadcasters' fixed TV viewing to free-form OTT viewing using wired and wireless internet. As a result, the ability to leverage data from OTT audiences has become critical to the competitiveness of the industry. However, third parties other than OTT content providers are facing difficulties in acquiring OTT viewer data. In this paper, as a way to overcome the shortcomings of existing viewer data acquisition, we propose a method to extract audio and video data by developing an OTT viewing data acquisition agent using Web APIs by adopting a web browser environment that does not affect the performance of OS and viewing devices, so that third-party companies that need viewing data can utilize it.

• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.422-435
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• 2005

Compared with analog broadcasting, digital broadcasting supports technical background to provide personalize the TV watching environment by offering broadcasting services that can adapt to viewers' preferences. However, current digital broadcasting shows limited services such as reservation recording, simple program guiding with an electronic program guide (EPG) on a personal video recorder system, and primitive data broadcasting by broadcasters. Therefore, the purpose of this paper is to suggest a new broadcasting environment which gives a person facility and a difference fur watching TV by serving enhanced personalized services. For that reason, we propose an intelligent broadcasting system which can minimize viewer's actions, and enhanced broadcasting services which are based on understanding of the semantics of broadcasting contents. To implement the system, agent technology as well as the MPEG-7 and TV-Anytime Forum (TVAF) are employed. For content-level services, real-time content filtering and personalized video skimming are designed and implemented. To verify the usefulness of the proposed system, we demonstrate it with a test-bed on which content-level personalized services are implemented.

• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.81-89
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• 2018

The purpose of this study is to classify the types of internet personal game broadcasting in China and to examine viewers' preferences type of it. By targeting top 100 creators of Player-Unknown's Battleground streaming as a personal game broadcaster with over 100,000 followers, the game types were classified based on the purpose and characteristic of game broadcasting such as game play, entertainment, and audience participation. As a result, the type of internet personal game broadcasting in China was classified into progamer type, cooperative playing type, storytelling type, and reciprocal entertainment type. The progamer type was 38% and it was the highest proportion of Player-Unknown's Battlegrounds streaming. Next came storytelling type, cooperative playing type and reciprocal entertainment type with 25%, 19% and 18% respectively. In sum, progamer type and storytelling type which shows relatively low real - time communication with audiences accounted for a high percentage of 63%. This implies that the characteristics of the broadcast media focused on 'showing' have influenced the production and planning of personal game broad casting. The interactive characteristics of the platform of personal game broad casting can be expected to gradually change the conventional customs of broadcasting media.

• Korean journal of communication and information
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• v.58
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• pp.154-177
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• 2012

Considering the growing importance of TV favorite channel setting function due to the rapid increase of number of TV channels, this study tried to find factors which affect the attitude toward and intention to use the favorite channel setting function. As related theories, this study used theory of diffusion of innovation, channel repertoire, channel changing behaviors, and social influences and suggested research hypotheses and questions based on the theories. After collecting data through online survey of 192 general audience, this study empirically analyzed the data by using multiple regression analysis. The result showed that innate innovativeness, relative advantage and social critical mass affected attitude toward using the favorite channel setting function and that compatibility, visibility, social critical mass influenced intention to use the function.