Sequential pattern mining aims to find frequent patterns (guarded by a minimum support) in a database of sequences. As the support decreases the number of sequential patterns will...
Previous study has shown that mining frequent patterns with length-decreasing support constraint is very helpful in removing some uninteresting patterns based on the observation t...
As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the req...
We define sporadic rules as those with low support but high confidence: for example, a rare association of two symptoms indicating a rare disease. To find such rules using the w...
The efficiency of frequent itemset mining algorithms is determined mainly by three factors: the way candidates are generated, the data structure that is used and the implementati...