A New Approach for Handling Numeric Ranges for Graph-Based Knowledge Discovery
Discovering interesting patterns from structural domains is an important task in many real world domains. In recent years, graph-based approaches have demonstrated to be a straight forward tool to mine structural data. However, not all graph-based knowledge discovery algorithms deal with numerical attributes in the same way. Some of the algorithms discard the numeric attributes during the preprocessing step. Some others treat them as alphanumeric values with an exact matching criterion, with the limitation to work with domains that do not have this type of attribute or discovering patterns without interesting numerical generalizations.