Topic discovery of web video using star-structured K-partite graph

As the explosive growth of web videos on video-shared sites like YouTube, the discovery of video topics has become a hot research area. In order to utilize all kinds of characteristics in web video such as visual features (SIFT, shape or color) and contextual cues (such as title or tags) effectively, this paper proposes an approach to represent the explicit and implicit correlations hidden in web videos by a star-structured K-partite graph model, and then a co-clustering process is conducted to discover video topics. The experimental results demonstrate the feasibility and effectiveness of the proposed approach.