Mining sequential movement patterns describing group behaviour in potentially streaming spatio-temporal data sets is a challenging problem. Movements are typically noisy and often...
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Traditional methods of association rule mining consider the appearance of an item in a transaction, whether or not it is purchased, as a binary variable. However, customers may pu...