Browse by Chunks: Topic Mining and Organizing on Web-Scale Social Media

The overwhelming amount of Web videos returned from search engines makes effective browsing and search a challenging task. Rather than conventional ranked list, it becomes necessary to organize the retrieved videos in alternative ways. In this article, we explore the issue of topic mining and organizing of the retrieved web videos in semantic clusters. We present a framework for clustering-based video retrieval and build a visualization user interface. A hierarchical topic structure is exploited to encode the characteristics of the retrieved video collection and a semi-supervised hierarchical topic model is proposed to guide the topic hierarchy discovery. Carefully designed experiments on web-scale video dataset collected from video sharing websites validate the proposed method and demonstrate that clustering-based video retrieval is practical to facilitate users for effective browsing.