Abstract
Querying and retrieving relevant information still remains a difficult task, one with a relatively high cognitive cost for users, who usually focus only on the first few pages of results. This issue drives effort to support the exploration of search results through clustering and visualization. This paper contributes to this challenge by providing a visual analytics system that is designed to support search tasks in multimedia document archives. The system provides complex querying, semantic overviews of time, and visual, and textual concepts combined with analysis. All search tasks are supported with linked-highlighting and leapfrog interactions. This is made possible all in a single data structure thanks to multilayer network modelling.
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