基于人工智能定制推荐服务的在线视频(OTT)内容制作技术比较

Sang-Hun Chun, Seoung-Jung Shin
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引用次数: 0

摘要

除了以Nexflix和YouTube为代表的OTT视频制作服务外,人工智能的个性化内容推荐系统也已经很普遍。YouTube的个性化推荐服务系统由两个神经网络组成,一个神经网络由推荐候选生成模型组成,另一个神经网络由排名网络组成。Netflix的视频推荐系统由两个数据分类系统组成,分为基于内容的过滤和协同过滤。随着新冠疫情激活网络平台主导的内容生产,利用人工智能的虚拟网红领域正在兴起。虚拟影响者是由GAN(生成对抗网络)人工智能产生的,并且是两个对立系统相互竞争的无监督学习算法。本研究还研究了未来开发基于个人推荐和虚拟网红(metabus)的AI平台作为OTT核心内容的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of online video(OTT) content production technology based on artificial intelligence customized recommendation service
In addition to the OTT video production service represented by Nexflix and YouTube, a personalized recommendation system for content with artificial intelligence has become common. YouTube's personalized recommendation service system consists of two neural networks, one neural network consisting of a recommendation candidate generation model and the other consisting of a ranking network. Netflix's video recommendation system consists of two data classification systems, divided into content-based filtering and collaborative filtering. As the online platform-led content production is activated by the Corona Pandemic, the field of virtual influencers using artificial intelligence is emerging. Virtual influencers are produced with GAN (Generative Adversarial Networks) artificial intelligence, and are unsupervised learning algorithms in which two opposing systems compete with each other. This study also researched the possibility of developing AI platform based on individual recommendation and virtual influencer (metabus) as a core content of OTT in the future.
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