Recent advances in domain-driven data mining

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Abstract

Data mining research has been significantly motivated by and benefited from real-world applications in novel domains. This special issue was proposed and edited to draw attention to domain-driven data mining and disseminate research in foundations, frameworks, and applications for data-driven and actionable knowledge discovery. Along with this special issue, we also organized a related workshop to continue the previous efforts on promoting advances in domain-driven data mining. This editorial report will first summarize the selected papers in the special issue, then discuss various industrial trends in the context of the selected papers, and finally document the keynote talks presented by the workshop. Although many scholars have made prominent contributions with the theme of domain-driven data mining, there are still various new research problems and challenges calling for more research investigations in the future. We hope this special issue is helpful for scholars working along this critically important line of research.

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Liu, C., Fakharizadi, E., Xu, T., & Yu, P. S. (2023, January 1). Recent advances in domain-driven data mining. International Journal of Data Science and Analytics. Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/s41060-022-00378-1

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