| 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.
|
