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Ontology driven contextual tagging of multimedia data

机译:本体驱动的多媒体数据上下文标记

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To exhibit multi-modal information and to facilitate people in finding multimedia resources, tagging plays a significant role. Various public events like protests and demonstrations are always consequences of break out of some public outrage resulting from prolonged exploitation and harassment. This outrage can be seen in news footage, blogs, text news and other web data. So, aggregating this variety of data from heterogeneous sources is a prerequisite step for tagging multimedia data with appropriate content. Since content has no meaning without a context, a video should be tagged with its relevant context and content information to assist user in multimedia retrieval. This paper proposes a model for tagging of multimedia data on the basis of contextual meaning. Since context is knowledge based, it has to be guided and learned by ontology which will help fragmented information to be represented in a more meaningful way. Our tagging approach is novel and has practical applicability in the sense that whenever a new video is uploaded on some media sharing site, the context and content information gets attached automatically to a video. Thus, providing relatively complete information associated with the video.
机译:为了展示多模式信息并帮助人们找到多媒体资源,标记起着重要的作用。诸如抗议和示威之类的各种公共事件始终是由于长期的剥削和骚扰而引起的一些公共愤怒的爆发。在新闻镜头,博客,文字新闻和其他网络数据中可以看到这种愤怒。因此,聚合来自异构源的各种数据是用适当的内容标记多媒体数据的前提步骤。由于没有上下文,内容没有任何意义,因此应使用相关的上下文和内容信息标记视频,以帮助用户进行多媒体检索。本文提出了一种基于上下文意义的多媒体数据标签模型。由于上下文是基于知识的,因此必须由本体来指导和学习,本体将帮助以更有意义的方式表示碎片化的信息。我们的标记方法是新颖的,在某种意义上说具有实用性,因为每当在某个媒体共享站点上上传新视频时,上下文和内容信息就会自动附加到视频上。因此,提供与视频相关的相对完整的信息。

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