Online web video topic detection and tracking with semi-supervised learning

With the pervasiveness of online social media and rapid growth of web data, a large amount of multimedia data is available online. However, how to organize them for facilitating users’ experience and government supervision remains a problem yet to be seriously investigated. Topic detection and tracking, which has been a hot research topic for decades, could cluster web videos into different topics according to their semantic content. However, how to online discover topic and track them from web videos and images has not been fully discussed. In this paper, we formulate topic detection and tracking as an online tracking, detection and learning problem. First, by learning from historical data including labeled data and plenty of unlabeled data using semi-supervised multi-class multi-feature method, we obtain a topic tracker which could also discover novel topics from the new stream data. Second, when new data arrives, an online updating method is developed to make topic tracker adaptab...

• Type: Journal
• Year: 2016
• Where: MMS
• Authors: Guorong Li, Shuqiang Jiang, Weigang Zhang, Junbiao Pang, Qingming Huang
• Keywords: Information Technology, MMS 2016