About the Journal

The Journal of Data Mining, Knowledge Discovery, and Decision Support Systems (JDMKD-DSS) is an authoritative platform for disseminating innovative research on extracting actionable insights from data and applying them to intelligent decision-making processes. The journal explores advanced techniques in data mining, machine learning, and statistical modeling, focusing on their application to complex real-world challenges in industries such as healthcare, finance, transportation, and e-commerce. A core focus of the journal is on the methodologies and algorithms that drive knowledge discovery from diverse datasets. Topics of interest include clustering, classification, association rule mining, anomaly detection, and graph mining. Papers that present novel hybrid approaches or optimize existing methods to handle large-scale, heterogeneous data are particularly welcome.