When Is the Right Time to Refresh Knowledge Discovered from Data?

Xiao Fang (), Olivia R. Liu Sheng () and Paulo Goes ()
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Xiao Fang: Department of Operations and Information Systems, David Eccles School of Business, University of Utah, Salt Lake City, Utah 84112
Olivia R. Liu Sheng: Department of Operations and Information Systems, David Eccles School of Business, University of Utah, Salt Lake City, Utah 84112
Paulo Goes: Department of Management Information Systems, Eller College of Management, University of Arizona, Tucson, Arizona 85721

Operations Research, 2013, vol. 61, issue 1, 32-44

Abstract: Knowledge discovery in databases (KDD) techniques have been extensively employed to extract knowledge from massive data stores to support decision making in a wide range of critical applications. Maintaining the currency of discovered knowledge over evolving data sources is a fundamental challenge faced by all KDD applications. This paper addresses the challenge from the perspective of deciding the right times to refresh knowledge. We define the knowledge-refreshing problem and model it as a Markov decision process. Based on the identified properties of the Markov decision process model, we establish that the optimal knowledge-refreshing policy is monotonically increasing in the system state within every appropriate partition of the state space. We further show that the problem of searching for the optimal knowledge-refreshing policy can be reduced to the problem of finding the optimal thresholds and propose a method for computing the optimal knowledge-refreshing policy. The effectiveness and the robustness of the computed optimal knowledge-refreshing policy are examined through extensive empirical studies addressing a real-world knowledge-refreshing problem. Our method can be applied to refresh knowledge for KDD applications that employ major data-mining models.

Keywords: data mining; knowledge discovery in databases; knowledge refreshing; Markov decision process (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (3)

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