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Commentary-based video categorization and concept discovery

机译:基于评论的视频分类和概念发现

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摘要

Social network contents are not limited to text but also multimedia. Dailymotion, YouTube, and MySpace are examples of successful sites which allow users to share videos among themselves. Due to the huge amount of videos, grouping videos with similar contents together can help users to search videos more efficiently. Unlike the traditional approach to group videos into some predefined categories, we propose a novel comment-based matrix factorization technique to categorize videos and generate concept words to facilitate searching and indexing. Since the categorization is learnt from users feedback, it can accurately represent the user sentiment on the videos. Experiments conducted by using empirical data collected from YouTube shows the effectiveness of our proposed methodologies.
机译:社交网络的内容不仅限于文本,还包括多媒体。 Dailymotion,YouTube和MySpace是成功网站的示例,这些网站允许用户彼此共享视频。由于视频量巨大,将内容相似的视频分组在一起可以帮助用户更有效地搜索视频。与将视频分为一些预定义类别的传统方法不同,我们提出了一种基于注释的新颖矩阵分解技术,可以对视频进行分类并生成概念词,以利于搜索和索引。由于分类是从用户反馈中获悉的,因此可以准确地表示视频上的用户情绪。使用从YouTube收集的经验数据进行的实验表明了我们提出的方法的有效性。

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