Mining Maximal Dense Intervals from Temporal Interval Data

Some real life data are associated with duration of events instead of point events. The most common example of such data is data of cellular industry where each transaction is associated with a time interval. Mining maximal fuzzy intervals from such data allows the user to group the transactions with similar behavior together. Earlier works were devoted to mining frequent as well as maximal frequent non-fuzzy intervals. We propose here a method of mining maximal dense fuzzy intervals where density of an interval quite similar to the frequency of an interval.