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 …

This study explored the global cyberspace security issues, with the purpose of breaking the
stereotype of people's cognition of cyberspace problems, which reflects the relationship …

Abstract The High Average Utility Itemset Mining (HAUIM) technique, a variation of High
Utility Itemset Mining (HUIM), uses the average utility of the itemsets. Historically, most …

High-utility pattern mining is an important sub-literature in the data mining literature. This
literature discusses the discovery of useful pattern information from large databases by …

Data mining has been actively studied, and it has become more important due to the
development of information technology and the demands of diverse applications, such as …

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 …

Periodic pattern mining is a topic for mining periodic event patterns with sufficient
confidence. The resulted patterns are often used to predict future events because they have …

Top-k high utility itemsets (HUIs) mining permits discovering the required number of patterns-
k, without having an optimal minimum utility threshold (ie, minimum profit). Multiple top-k …

Osteoarthritis (OA) is a degressive and complex disease which is a growing public health
problem on a global scale. On basis of an in-house database consisting of clinical records of …

Utility pattern mining is a branch of data mining that extracts valid patterns by considering
the quantity and weight of the items. In addition, utility occupancy pattern mining, which …