Data Visualization
Text analysis is often mentioned in the same sentence as information (or data) visualization, in large part because visualization is one of the viable technical tools for information analysis after unstructured information has been structured.
The example below shows how ZyLAB search results can be plotted on a Google Map to show their geographic locations. The image displays the document properties selected by the user and provides a link to open the actual document.
In the second data visualization example below, the user is viewing search results for the word “ZyLAB” as an interactive hyperbolic tree. The user may click and drag the star to reveal the different relationships between the search hits, its properties, and its location.
Another visualization approach is a TreeMap in which an archive is presented as a grid. The components of the grid are color-coded and sized based upon their interrelationships and content volume. This structure allows you to get a quick visual representation of areas with the most entities. A value can also be allocated to a certain type of entity, such as the size of an e-mail or a file.
These types of visualization techniques are ideal for allowing an easy insight into large e mail collections. Alongside the structure that text analysis techniques can deliver, use can also be made of the available attributes such as “Sender”, “Recipient”, “Subject”, “Date”, etc.
