Graph data is found in numerous domains such as for the analysis of social networks,
sensor networks, bioinformatics, industrial systems, and chemistry. Analyzing graphs to …

Nonoverlapping sequential pattern mining is an important type of sequential pattern mining
(SPM) with gap constraints, which not only can reveal interesting patterns to users but also …

Sequential pattern mining (SPM) has been applied in many fields. However, traditional SPM
neglects the pattern repetition in sequence. To solve this problem, gap constraint SPM was …

Nonoverlapping sequential pattern mining (SPM) is a data analysis task, which aims at
identifying repetitive sequential patterns with gap constraint in a set of discrete sequences …

One-off sequential pattern mining (SPM)(or SPM under the one-off condition) is a kind of
repetitive SPM with gap constraints, and has been widely applied in many fields. However …

Gap constraint sequential pattern mining (SPM), as a kind of repetitive SPM, can avoid
mining too many useless patterns. However, this method is difficult for users to set a suitable …

Nonoverlapping sequential pattern mining, as a kind of repetitive sequential pattern mining
with gap constraints, can find more valuable patterns. Traditional algorithms focused on …

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 …

Repetitive sequential pattern mining (SPM) with gap constraints is a data analysis task that
consists of identifying patterns (subsequences) appearing many times in a discrete …

The current research investigated the telecommunication subscriber data in 2020 from the
system report of Nigeria Communication Commission (NCC), which revealed that Nigerian …