Constraints applied on classic frequent patterns are too strict and may cause interesting patterns to be missed. Hence, researchers have proposed to mine a more relaxed version of...
Frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. However, the bottleneck of...
Levelwise algorithms (e.g., the Apriori algorithm) have been proved eective for association rule mining from sparse data. However, in many practical applications, the computation ...
Mining fault tolerant (FT) frequent patterns from transactional datasets are very complex than mining all frequent patterns (itemsets), in terms of both search space exploration a...
In this paper, we propose a set of novel regression-based approaches to effectively and efficiently summarize frequent itemset patterns. Specifically, we show that the problem of ...