Periodic-frequent patterns (or itemsets) are an important class of regularities that exist in a
transactional database. Finding these patterns involves discovering all frequent patterns that …

Periodic pattern mining is a popular data mining task, which consists of identifying patterns
that periodically appear in data. Traditional periodic pattern mining algorithms are designed …

Discovering periodic-frequent patterns in temporal databases is a challenging problem of
great importance in many real-world applications. Though several algorithms were …

Over the past two decades, numerous algorithms have been proposed for mining frequent
itemsets from precise data. However, there are situations in which data are uncertain. In …

Frequent pattern mining is commonly used in many real-life applications. Since its
introduction, the mining of frequent patterns from precise data has drawn attention of many …

Time and frequency are two important dimensions to determine the interestingness of a
pattern in a database. Periodic-frequent patterns are an important class of regularities that …

Stable periodic-frequent itemset mining is essential in big data analytics with many real-
world applications. It involves extracting all itemsets exhibiting stable periodic behaviors in a …

Periodic-frequent patterns are an important class of regularities that exist in a transactional
database. Informally, a frequent pattern is said to be periodic-frequent if it appears at a …

A temporal database is a collection of transactions, ordered by their timestamps. Discovering
partial periodic itemsets in temporal databases has numerous applications. However, to the …

Periodic pattern mining is an emerging technique for knowledge discovery. Most previous
approaches have aimed to find only those patterns that exhibit full (or perfect) periodic …