Domain driven data mining

It studies the corresponding foundations, frameworks, algorithms, models, architectures, and evaluation systems for actionable knowledge discovery.

[1][2] Data-driven pattern mining and knowledge discovery in databases[3] face such challenges that the discovered outputs are often not actionable.

A significant paradigm shift is the evolution from data-driven pattern mining to domain-driven actionable knowledge discovery.

Domain driven data mining has attracted significant attention from both academic and industry.

[16] Actionable insight enables accurate and in-depth understanding of things or objects and their characteristics, events, stories, occurrences, patterns, exceptions, and evolution and dynamics hidden in the data world and corresponding decision-making actions on top of the insights.