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- W3142974690 abstract "The data mining process consists of a series of steps ranging from data cleaning, data selection and transformation, to pattern evaluation and visualization. One of the central problems in data mining is to make the knowledge actionable. Here the term actionable refers to the mined patterns suggest concrete and profitable actions to the decision-maker. In this paper, we present a formal view of actionable knowledge discovery (AKD) from the system and decision-making perspectives. AKD is a closed optimization problem- solving process from problem definition, framework/model design to actionable pattern discovery, and is designed to deliver operable business rules that can be seamlessly associated or integrated with business processes and systems. To support such processes, we correspondingly propose, formalize, and illustrate Multisource Combined-Mining-based AKD (MSCM-AKD). A real-life case study of MSCM-based AKD is demonstrated to extract debt prevention patterns from social security data. Substantial experiments show that the proposed frameworks are sufficiently general, flexible, and practical to tackle many complex problems and applications by extracting actionable deliverables for instant decision-making." @default.
- W3142974690 created "2021-04-13" @default.
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- W3142974690 date "2012-01-01" @default.
- W3142974690 modified "2023-09-26" @default.
- W3142974690 title "Actionable Knowledge Discovery" @default.
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