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Enriching Information Technology Research for Each Video Contents Scene Based on Semantic Social Networking Using Ontology-Learning

机译:基于在本体学习的语义社交网络的每个视频内容场景丰富信​​息技术研究

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There are a lot of contents currently, so user want to search their demanded scene. However, User can get their want information to be provided by information provider. In other words, users spend a lot of time to search their demanded scene. Solving this problem, this paper suggests methods searching based on semantic for each scene of video contents, and spreading knowledge service. We composed tagging and marking about things that appeared in video contents, using open-source. And we designed metadata and metadata system for explaining video contents, then we tagged information of things that composed with scene of video contents using this.
机译:目前有很多内容,所以用户想要搜索他们要求的场景。但是,用户可以通过信息提供商提供他们想要提供的信息。换句话说,用户花了很多时间来搜索他们所要求的场景。解决这个问题,本文建议基于对视频内容的每个场景的语义进行搜索,并传播知识服务。我们使用开源编写了关于视频内容中出现的事物的标记和标记。我们设计了元数据和元数据系统,用于解释视频内容,然后我们使用此标记使用视频内容场景的事物的信息。

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