文章基本信息

标题：Automatic Mining in Ontology Based Fuzzy Video Semantic Content Model
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作者：M.Abinaya ; R.Kiruthiga ; A.Kiruthika 等
期刊名称：International Journal of Communication and Computer Technologies
印刷版ISSN：2278-9723
出版年度：2014
卷号：2
期号：2
出版社：IJCCTS
摘要：The video based applications are in the need of extracting the video contents. The video contains various features which can be classified into normal data, relative features and logic content. The first two levels are insufficient to fulfill the user needs. To understand the core content of video, semantic level is required. Manual techniques will build a gap between these levels. So, it is not efficient. VISCOM is a video semantic content model and it contains classes and relations. Semantic content types such as objects and events are represented by some VISCOM classes and other classes are used in the automatic semantic content extraction framework. The semantic content types and relations are collected under VISCOM classes. In this proposed system, the user allowed to query and retrieve the objects, events, concepts. Those are extracted automatically by using semantic content algorithm and rule definitions. The result will be generated in the graphical manner. By the use of graphical output, the level of performance achieved by the extraction process will be predicted
关键词：Ontology; VISCOM; Fuzziness; Semantic content extraction; Rule definitions