Data uncertainty has been taken into a consideration for mining and discovery of its hidden
knowledge in a variety of applications. Due to the fact that the nature of closed sequences is …

Enumerating maximal bicliques in a bipartite graph is an important problem in data mining,
with many applications across different domains such as web community, bioinformatics, etc …

In some situations, finding the rare association rule is of higher importance than the frequent
itemset. Unique rules represent rare cases, activities, or events in real-world applications. It …

High utility itemset mining considers unit profits and quantities of items in a transaction
database to extract more applicable and more useful association rules. Downward closure …

In the Internet age, analyzing the behavior of online users can help webstore owners
understand customers' interests. Insights from such analysis can be used to improve both …

Spatio-temporal mobility patterns are at the core of strategic applications such as urban
planning and monitoring. Depending on the strength of spatio-temporal constraints, different …

Frequent closed itemsets provide a lossless and concise collection of all frequent itemsets to
reduce the runtime and memory requirement of frequent itemsets mining tasks. This study …

This paper explores five pattern mining problems and proposes a new distributed framework
called DT-DPM: Decomposition Transaction for Distributed Pattern Mining. DT-DPM …

The problem of mining frequent weighted itemsets (FWIs) is an extension of the mining
frequent itemsets (FIs), which considers not only the frequent occurrence of items but also …

Mining of colossal patterns is used to mine patterns in databases with many attributes and
values, but the number of instances in each database is small. Although many efficient …