Association rules are commonly used to provide decision‐makers with knowledge that helps
them to make good decisions. Most of the published proposals mine association rules …

This paper presents a neural network approach for weather forecast improvement. Predicted
parameters, such as air temperature or precipitation, play a crucial role not only in the …

Abstract Frequent Sequence Mining (FSM) is a fundamental task in data mining. Although
FSM algorithms extract frequent patterns, they cannot discover patterns that periodically …

Periodic itemset mining is the task of finding all the sets of items (events or symbols) that
regularly appear in a sequence. One of the most important applications is customer behavior …

Periodic frequent pattern mining (PFPM) with temporal regularity is an emerging field in data
mining. The user-defined maximum periodicity threshold restricts most of the existing PFPM …

Discovering periodic patterns in data is an important data analysis task. A periodic pattern is
a set of values that regularly appear together over time. Finding such patterns can be useful …

Periodic frequent pattern mining (PFPM) is an emerging topic in data mining. Periodicity of a
pattern expresses its regularity in the transactional database. Existing PFPM approaches do …

Periodic frequent pattern mining (PFPM) is an emerging topic in data mining. Periodicity of a
pattern expresses its regularity in the transactional database. Existing PFPM approaches do …

The availability of modern technology and the recent proliferation of devices and sensors
have resulted in a tremendous amount of data being generated, stored and handled in …