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LegendBurster Features

LegendBurster's features are demonstrated in the Animated Tutorial.

They are described in detail in the comprehensive System Documentation which is included with LegendBurster, and available for review by clicking here.

LegendBurster Semantic Nets are ideally suited for the management of:

  • Hierarchically structured information, such as scientific classification systems
    < View Example >

  • Open-ended lists of attribute values
    < View Example>

  • Features which are explicitly negated or declared to be absent <Explanation>

LegendBurster query results include scored partial matches in addition to exact query matches  -  often a critical advantage during exploratory data analysis <Example>. Weightings for the partial matches take into account the three data management issues mentioned above in a fully-auditable manner which includes an interactive explanation facility <Example>. 

At the heart of LegendBurster lies the Matcher, which is described in detail in a technical paper presented here.

 

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Last modified: 03/29/08.