A Methodological View on Knowledge-Intensive Subgroup Discovery

  • Martin Atzmueller
  • Frank Puppe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4248)


Background knowledge is a natural resource for knowledge-intensive methods: Its exploitation can often improve the quality of their results significantly. In this paper we present a methodological view on knowledge-intensive subgroup discovery: We introduce different classes and specific types of useful background knowledge, discuss their benefit and costs, and describe their application in the subgroup discovery setting.


Background Knowledge Medical Domain Priority Group Subgroup Discovery Aggregation Constraint 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Martin Atzmueller
    • 1
  • Frank Puppe
    • 1
  1. 1.Department of Computer ScienceUniversity of WürzburgWürzburgGermany

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