Data mining is the process of extracting useful unknown knowledge from large datasets.
Frequent itemset mining is the fundamental task of data mining that aims at discovering …

In recent years, rare pattern mining has shown great vitality in some real-world fields, such
as disease diagnosis, criminal behavior analysis, anomaly detection in networks, and so on …

Over the past era, Frequent Pattern Mining (FPM) is emerging as a significant approach to
discover fascinating knowledge concealed in the data. However, preceding works failed to …

With the emergence of webpage services, huge amounts of customer transaction data are
flooded in cyberspace, which are getting more and more useful for profiling users and …

In this work, a Multi-Objective Evolutionary Algorithm (MOEA) is developed to identify
Functional Dependencies (FDEPs) in Complex Technical Infrastructures (CTIs) from alarm …

Functional dependencies in complex technical infrastructures can cause unexpected
cascades of failures. Given the complexity and continuous evolution in time of the …

The paper explores the domain of lossy compression, specifically incorporating data mining
techniques in the process of image encoding. Clustering is employed to group similar pixels …

Abstract A Multi-Objective Evolutionary Algorithm (MOEA) is proposed for the identification of
association rules describing functional dependencies in Complex Technical Infrastructures …