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@TECHREPORT{kauschka2009studienarbeit,
       author = {Kauschka, Stephan},
        month = dec,
        title = {Analyzing the Similarity of Association Rules over Time},
         year = {2009},
  institution = {Otto-von-Guericke-Universit{\"{a}}t Magdeburg},
     abstract = {Many companies nowadays collect huge amount of data which have to be analyzed in
order to gain crucial advantages in highly competitive market environments. Association
rule change mining has been suggested as one technique to cover this task. The amount
of the resulting association rules however is usually too vast to be investigated manually.
This thesis reviews the use of distance measures in order to help human experts to find
interesting rules and suggests own measures for this task. It especially focuses on the
use of rule histories for those distance measures. The use of the interchange format
PMML to incorporate the distance measures is investigated. The results finally were
implemented in a software called IDEAL.}
}