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 …

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

Sequential Pattern Mining (SPM) is a branch of data mining that deals with finding
statistically relevant regularities of patterns in sequentially ordered data. It has been an …

The problem of mining high utility sequences aims at discovering subsequences having a
high utility (importance) in a quantitative sequential database. This problem is a natural …

Negative sequential patterns (NSPs) produced by negative sequence analysis (NSA)
capture more informative and actionable knowledge than classic positive sequential …

Negative sequential pattern mining (SPM) is an important SPM research topic. Unlike
positive SPM, negative SPM can discover events that should have occurred but have not …

Abstract High Utility Pattern Mining is a popular task for analyzing data. It consists of
discovering patterns having a high importance in databases. A popular application of high …

Business process analysis is a key activity that aims at increasing the efficiency of business
operations. In recent years, several data mining based methods have been designed for …

Pattern mining has been an attractive topic for many researchers since its first introduction.
Clickstream mining, a specific version of sequential pattern mining, has been shown to be …