News videos contain huge amount of daily information, in which there is a great deal of redundancy and repetition content. Thus it is necessary to analyze news stories’ relationships and generate news topic effectively. This research proposes an approach for generating news video event topic based on stories. K-means cluster algorithm was used to group topic-evolving stories integrating textual and visual features. Based on the similarity and dependency between stories, an event topic was constructed automatically for the news video topic organization and threading. Finally, the generated event topic structure was visualized in event-time space. Experimental results show that the topic structure generated by the proposed approach can facilitate the fast navigation and understanding of the news topic.