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Metadata extraction and classification of YouTube videos using sentiment analysis

机译:使用情感分析对YouTube视频进行元数据提取和分类

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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,并在促进可互操作的服务方面取得了很大的成功,该互操作的服务可将视频提供给各种设备上的消费者。但是,媒体消费已不仅仅是媒体资产的回放,而且还面向依赖丰富元数据和内容描述的更丰富的用户体验。本文提出了一种从视频中提取和分析元数据,然后进行与视频内容相关的决策的技术。系统将情感分析用于此类分类。可以设想,该系统在全面开发后将用于确定Web上非法多媒体内容的存在。

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