Knowledge Discovery and Data Mining

  • Jan Fabian Ehmke
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 177)


Nowadays, it is possible to collect detailed data about the current state and the operations of systems such as transportation systems. Due to technological advancements, we may collect and store enormous amounts of operational data at low costs. These data are usually not properly exploited, because the derivation of relevant information for the improvement of planning systems is challenging. However, planning systems rely on such information describing the typical behavior of a system, which can be derived from aggregates of operational data. Based on typical system behavior, future operations can be planned.


Cluster Algorithm Data Object Cluster Approach Information Model Mass Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.Carl-Friedrich Gauss Department of EconomicsUniversity of BraunschweigBraunschweigGermany

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