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A Study on the OTT Consumer Classification Based on Artificial Intelligence
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인공지능 기술 기반 OTT 사용자 분석 방안

논문 기본 정보

Type
Academic journal
Author
Jaeun Choi (경일대학교)
Journal
한국산업경영학회 경영연구 경영연구 제35권 제5호 KCI Accredited Journals
Published
2020.1
Pages
115 - 128 (14page)

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A Study on the OTT Consumer Classification Based on Artificial Intelligence
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As the use of OTT such as YouTube and Netflix is increasing rapidly, the media and network market is also changing rapidly. In particular in the case of network operators, as the traffic caused by OTT increases rapidly, it has become essential to analyze the OTT traffic of consumers in pricing plans and infrastructure investment. In addition, companies that provide OTT also help establish management strategies such as providing their own proprietary content and paying network usage fees for OTT users. In this study, we propose a method to analyze users by analyzing the traffic of OTT users. First of all, we classified users based on machine learning techniques that are traditionally used for user classification. In addition, a method for classifying OTT users through deep learning techniques, which has recently attracted attention in various fields, has also been proposed. When analyzing users based on machine learning, it was confirmed that analysis was possible in a relatively fast time while showing high accuracy. When analyzing OTT users using deep learning, it can be seen that the accuracy is higher than that of existing machine learning techniques. The techniques proposed in this study enable network operators and OTT operators to more accurately classify OTT users, enabling them to set customized plans, invest in efficient infrastructure and discover competitive content. In addition, it has been confirmed that OTT user analysis is possible through deep learning, so many operators will be able to use deep learning when accurate analysis is required.
#OTT #사용자 분석 #머신러닝 #딥러닝

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