Abstract
The success of data mining learned rules highly depends on its actionability: how useful it is to perform suitable actions in any real business environment. To improve rule actionability, different researchers have initially presented various Data Mining (DM) frameworks by focusing on different factors only from the business domain dataset . Afterward, different Domain-Driven Data Mining (D3M) frameworks were introduced by focusing on domain knowledge factors from the context of the overall business environment. Despite considering these several dataset factors and domain knowledge factors in different phases of their frameworks, the learned rules still lacked actionability. The objective of our research is to improve the learned rules’ actionability. For this purpose, we have analyzed: (1) what overall actions or tasks are being performed in the overall business process, (2) in which sequence different tasks are being performed, (3) under what certain conditions these tasks are being performed, (4) by whom the tasks are being performed (5) what data is provided and produced in performing these tasks. We observed that the inclusion of rule learning factors only from dataset or from domain knowledge is not sufficient. Our Process-based Domain-Driven Data Mining-Actionable Knowledge Discovery (PD3M-AKD) framework explains its different phases to consider and include additional factors from five perspectives of the business process. This PD3M-AKD framework is also in line with the existing phases of current DM and D3M frameworks for considering and including dataset and domain knowledge accordingly. Finally, we evaluated and validated our case study results from different real-life scenarios from education, engineering, and business process domains at the end.
Highlights
In today’s competitive and dynamic business environment, the discovery of actionable knowledge has become an exhaustive task as data mining frameworks were and are still concentrating on considering dataset factors, i.e., data types, dimensions, quality of data, etc. from dataset alone to take organizational business decisions [1]
Question 1, what overall actions or tasks are being performed in the overall business process
Results showed that process-based factors, i.e., what overall actions being performed in the educational process, impact a lot while evaluating students' performance conferring to the contexts
Summary
In today’s competitive and dynamic business environment, the discovery of actionable knowledge has become an exhaustive task as data mining frameworks were and are still concentrating on considering dataset factors, i.e., data types, dimensions, quality of data, etc. from dataset alone to take organizational business decisions [1]. In today’s competitive and dynamic business environment, the discovery of actionable knowledge has become an exhaustive task as data mining frameworks were and are still concentrating on considering dataset factors, i.e., data types, dimensions, quality of data, etc. The discovery of actionable knowledge highly depends upon the learned rules that can directly or explicitly determine the specific context that leads to actions. Actionability determines how much these contextual learned rules are useful for making actionable decisions in a real business environment [6]. To make organizational decisions by concentrating and considering only the datasets through data mining (academia proposed) frameworks may silo mislead the actual representation owing to the absence of contextual part about the business domain according to which data was created
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