Objective: Association rule mining is one of the data mining process for discovering frequent
item set between transaction databases. The main objective of this research work is …

The support and periodicity are two important dimensions to determine the interestingness
of a pattern in a dataset. Periodic-frequent patterns are an important class of regularities that …

Correlated pattern mining has become increasingly an important task in data mining and
knowledge discovery. In practice, the exploitation of correlated patterns is hampered by the …

Periodic-frequent pattern mining is an important model in data mining. The popular adoption
and successful industrial application of this model has been hindered by the following two …

In knowledge discovery studies, association rules mining has been extensively studied to
discover hidden knowledge and relationships among set of items in a transactional dataset …

Most data mining algorithms aim at discovering customer models and classification of
customer profiles. Application of these data mining techniques to industrial problems such …

In the literature about association analysis, many interestingness measures have been
proposed to assess the quality of obtained association rules in order to select a small set of …

Measures of interestingness play a crucial role in association rule mining. An important
methodological problem, on which several papers appeared in the literature, is to provide a …

Association rule mining from the large transactional database is one of the interesting and
challenging paradigms in knowledge discovery. An objective measure is a key tool for the …

Objective interestingness measures play a vital role in association rule mining of a large-
scaled database because they are used for extracting, filtering, and ranking the patterns. In …