About the Journal

The Journal of Data Intelligence and Applied Machine Learning (JDIAML) serves as an international forum for researchers and practitioners developing intelligent methods to extract value from data, with a particular focus on textual, behavioral, and multimodal datasets. The journal places a premium on research that advances robust algorithms, establishes sound evaluation processes, and yields reproducible results.

The Journal of Data Intelligence and Applied Machine Learning (JDIAML) disseminates original research articles, review articles, and short communications in the domains of data mining, machine learning, natural language processing, and applied AI. The journal places particular emphasis on unsupervised learning and weak-label settings.