Weighted Frequent Regular Pattern Mining
Weighted frequent regular pattern mining involves the discovery of regular patterns in a dataset where items are assigned different weights based on their significance. Regular patterns are sequences of itemsets that occur frequently and exhibit a regular or repeating structure. In weighted frequent regular pattern mining, the significance of a pattern is determined not only by its frequency but also by the cumulative weights of its constituent itemsets.
Applications: Retail Analytics, Healthcare Data Analysis, Manufacturing Process Optimization.