Visualizing published metadata in large aggregations
Much current research on digital libraries focuses on named entityextraction and transformation into structured information. Examples include entities like events, people, and places, and attributes like birth date or latitude. This video demonstration illustrates the potential for finding relationships among entities extracted from 50,000 news segments from CMUs Informedia Digital Video Library. A visual query language is used to specify relationships among entities. Data populate the query structure, which becomes an interface for exploration that gives continuous feedback in the form of visualizations of summary statistics. The target user is a data analyst familiar with the domain from which the entities come, but not a computer scientist.
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