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You’ve Data Mined. Now What?

机译:您已进行数据挖掘。怎么办?

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摘要

Data-mining technologies are within the grasp of many organizations. Commercially available data-mining packages make it relatively easy for firms to transform their data resources into predictive models. Yet, despite technological advances, the precise manner in which data-mining output should be incorporated into an organization’s decision-making processes remains unclear. This paper attempts to clarify the role of data mining by situating it within the context of Simon’s model of decision making. We use a complex decision problem from the video game development industry to illustrate several practical challenges managers face when using data-mining output as a decision making input. We then show how some of these challenges can be overcome by incorporating data-mined predictive models into a conventional decision-analytic formulation of the problem.
机译:数据挖掘技术是许多组织所掌握的。商业上可用的数据挖掘程序包使公司相对容易地将其数据资源转换为预测模型。然而,尽管技术进步,但仍不清楚将数据挖掘输出合并到组织的决策过程中的确切方式。本文试图通过将数据挖掘置于Simon的决策模型环境中来阐明其作用。我们使用视频游戏开发行业中的一个复杂决策问题来说明管理人员在将数据挖掘输出用作决策输入时面临的一些实际挑战。然后,我们展示了如何通过将数据挖掘的预测模型合并到问题的常规决策分析公式中来克服这些挑战。

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