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Metadata extraction and classification of YouTube videos using sentiment analysis

机译:使用情感分析的元数据提取与YouTube视频的分类

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MPEG media have been widely adopted and is very successful in promoting interoperable services that deliver video to consumers on a range of devices. However, media consumption is going beyond the mere playback of a media asset and is geared towards a richer user experience that relies on rich metadata and content description. This paper proposes a technique for extracting and analysing metadata from a video, followed by decision making related to the video content. The system uses sentiment analysis for such a classification. It is envisaged that the system when fully developed, is to be applied to determine the existence of illicit multimedia content on the Web.
机译:MPEG媒体已被广泛采用,并且非常成功地促进将视频提供视频到消费者的可互操作性服务。然而,媒体消费超出了媒体资产的播放,并且旨在依赖于丰富的元数据和内容描述的更丰富的用户体验。本文提出了一种用于从视频中提取和分析元数据的技术,然后是与视频内容相关的决策。该系统对这种分类使用情感分析。设想,系统在完全开发时,将应用于确定网上非法多媒体内容的存在。

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