News Rover: Exploring Topical Structures and Serendipity in Heterogeneous Multimedia News

News stories are rarely understood in isolation. Every story is driven by key entities that give the story its context. Persons, places, times, and several surrounding topics can often succinctly represent a news event, but are only useful if they can be both identified and linked together. We introduce a novel architecture called News Rover for re-bundling broadcast video news, online articles, and Twitter content. The system utilizes these many multimodal sources to link and organize content by topics, events, persons and time. We present two intuitive interfaces for navigating content by topics and their related news events as well as serendipitously learning about a news topic. These two interfaces trade-off between user-controlled and serendipitous exploration of news while retaining the story context. The novelty of our work includes the linking of multi-source, multimodal news content to extracted entities and topical structures for contextual understanding, and visualized in intuitive active and passive interfaces.