A workflow is a partial or total automation of a business process,<BR>in which a collection of \emph{activities} must be executed by<BR>humans or machines, according to certain procedural rules. This<BR>paper deals with an aspect of workflows which has not so far<BR>received much attention: providing facilities for the human system<BR>administrator to monitor the actual behavior of the workflow<BR>system in order to predict the ``most probable'' workflow<BR>executions. In this context, we develop a data mining algorithm<BR>for identifying frequent patterns, i.e., the workflow<BR>substructures that have been scheduled more frequently by the<BR>system. Several experiments show that our algorithm outperforms<BR>the standard approaches adapted to mining frequent instances.
Mining Frequent Instances on Workflows
2003
Abstract
A workflow is a partial or total automation of a business process,in which a collection of \emph{activities} must be executed by
humans or machines, according to certain procedural rules. This
paper deals with an aspect of workflows which has not so far
received much attention: providing facilities for the human system
administrator to monitor the actual behavior of the workflow
system in order to predict the ``most probable'' workflow
executions. In this context, we develop a data mining algorithm
for identifying frequent patterns, i.e., the workflow
substructures that have been scheduled more frequently by the
system. Several experiments show that our algorithm outperforms
the standard approaches adapted to mining frequent instances.
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