The Development of the Bi-directionally Personalized Broadcasting and the Targeting Advertisement System Based on the User Profile Techniques

Shin, Saim; Lee, Jong-Soel; Jang, Se-Jin; Lee, Soek-Pil

doi:10.5909/jbe.2010.15.5.632

Cited by 3 publications

(3 citation statements)

References 1 publication

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“…Therefore, as the amount of data increases rapidly, not only require a technique for classifying data, it is necessary services that can easily find the data to users who are using the Internet [6]. In developed countries already big data such as the United States and Europe, companies of course, is raising the heat in interest and investment in order to obtain useful information and value to society and humanity [7,8]. Companies can analyze the user's preference.…”

Section: Introductionmentioning

confidence: 99%

Big Data Collection Study for Providing Efficient Information

Yun¹,

Park²,

Hwang³

et al. 2015

IJSEIA

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Many data on smartphones and Internet development is communicated indiscriminately, thereby undergoing a rapid increase in data traffic. Especially in social commerce, the enormous information, the user becomes difficult yourself to find the necessary information. Even a company that provides the service, became difficult to be provided to understand the user needs information. Data that is not classified as an increase in senseless amount of data has become a new problem of this age. And is only collect the required data through the analysis, if the exact customized service is provided, it will be able to resolve the data traffic problems. Therefore, in this paper, we describe an efficient method of collecting big data to you customized advertising service users.

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Section: Introductionmentioning

confidence: 99%

Big Data Collection Study for Providing Efficient Information

Yun¹,

Park²,

Hwang³

et al. 2015

IJSEIA

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“…콘텐츠 [4][5] . 넥소피아가 캐나다에서 [6] , 비 보 [7] , Hi5, 마이스페이스, dol2day, Tagged, XING [8] , Skyrock 가 유럽에서 [9] , Orkut 및 Hi5가 남아메리카 및 중 아메리카에서 [10] [11] .…”

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“…TV Anytime의 표준을 바탕으로 개인프로파일과 콘텐츠의 메타데이터를 이용해서 매칭시키는 방법들이 많이 진행되 어 왔다[11] .본 논문에서는 사용자의 프로파일과 함께 멀티미디어 콘 텐츠를 소비하는 패턴을 바탕으로 유사한 사용자를 묶어주 그림 1. 소셜 네트워크 기반 콘텐츠 추천 시스템 개념도 Fig.…”

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Personalized Contents Recommendation System Based on Social Network

Lee¹

2013

Journal of Broadcast Engineering

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Patterns for generating and consuming contents are various in these days from conventional broadcasting contents to UCC. There are many researches on developing recommendation engines based on user's profile for providing desired contents. In this paper we propose a contents recommendation system using not only user's profile but other's profiles in closed user group of the social network based on patterns for user's consuming contents. The proposed recommendation agent update user's profile using usage history and other's profiles related to the user in the closed user group.

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Metadata Management System Implementation for Object-oriented Personalized Media Service based on Multiple Camera

Byun¹,

Lee²,

Lee³

2014

Journal of Broadcast Engineering

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Since digital broadcasting service has been begun, user's requirements have been increased for personalized broadcasting system that users can watch the part of programs which they want to watch in anytime. In personalized broadcasting system, metadata is important for searching program information based on user's input data. In this paper, an object-oriented media service metadata management module is implemented. Metadata used in this system is described by extending TV-Anytime specifications which is the International standard for personalized media service. For this, extended segments information is provided including object information which do not existing in previous personalized broadcasting standard. This system can provide better satisfaction to users by using object segmentation information.

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The Development of the Bi-directionally Personalized Broadcasting and the Targeting Advertisement System Based on the User Profile Techniques

Cited by 3 publications

References 1 publication

Big Data Collection Study for Providing Efficient Information

Big Data Collection Study for Providing Efficient Information

Personalized Contents Recommendation System Based on Social Network

Metadata Management System Implementation for Object-oriented Personalized Media Service based on Multiple Camera

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