本体驱动的多媒体数据上下文标记

N. Pahal, S. Chaudhury, Brejesh Lall
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引用次数: 1

摘要

为了展示多模态信息,方便人们查找多媒体资源,标记起着重要的作用。抗议和示威等各种公共事件总是由于长期的剥削和骚扰而引起的一些公愤爆发的结果。这种愤怒可以在新闻镜头、博客、文本新闻和其他网络数据中看到。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先决条件。由于内容没有上下文就没有意义,因此视频需要标记相关的上下文和内容信息,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注模型。由于上下文是基于知识的,因此它必须由本体来引导和学习,这将有助于碎片化信息以更有意义的方式表示。我们的标签方法是新颖的,并且具有实际的适用性,因为每当一个新的视频上传到一些媒体分享网站上时,上下文和内容信息就会自动附加到视频上。从而提供了相对完整的与视频相关的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ontology driven contextual tagging of multimedia data
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.
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