Periodic frequent patterns are sets of events or items that periodically appear in a sequence
of events or transactions. Many algorithms have been designed to identify periodic frequent …

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 …

Discovering periodic patterns consists of identifying all sets of items (values) that periodically
co-occur in a discrete sequence. Although traditional periodic pattern mining algorithms …

Periodic pattern mining has become a popular research subject in recent years; this
approach involves the discovery of frequently recurring patterns in a transaction sequence …

Periodic frequent pattern discovery is a non-trivial task to discover frequent patterns based
on user interests using a periodicity measure. Although conventional algorithms for periodic …

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

Mining high-utility patterns in databases containing items with both positive and negative
profits is useful in market basket databases, since negative profits are common in the real …

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 …

Abstract Periodic-Frequent Pattern Mining (PFPM) is an emerging problem, which consists
of identifying frequent patterns that periodically occur over time in a sequence of events …

The discovery of high-utility itemsets (HUIs) in transactional databases has attracted much
interest from researchers in recent years since it can uncover hidden information that is …