Not logged in.

Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Data mining workflow templates for intelligent discovery assistance and auto-experimentation
Organization Unit
  • Jörg-Uwe Kietz
  • Floarea Serban
  • Abraham Bernstein
  • Simon Fischer
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
  • English
Page Range 1 - 12
Event Title Proc of the ECML/PKDD'10 Workshop on Third Generation Data Mining: Towards Service-oriented Knowledge Discovery (SoKD'10)
Event Type workshop
Event Location Barcelona, Spain
Event Start Date September 20 - 2010
Event End Date September 24 - 2010
Abstract Text Knowledge Discovery in Databases (KDD) has grown a lot during the last years. But providing user support for constructing workflows is still problematic. The large number of operators available in current KDD systems makes it difficult for a user to successfully solve her task. Also, workflows can easily reach a huge number of operators(hundreds) and parts of the workflows are applied several times. Therefore, it becomes hard for the user to construct them manually. In addition, workflows are not checked for correctness before execution. Hence, it frequently happens that the execution of the workflow stops with an error after several hours runtime. In this paper we present a solution to these problems. We introduce a knowledge-based representation of Data Mining (DM) workflows as a basis for cooperative interactive planning. Moreover, we discuss workflow templates, i.e. abstract workflows that can mix executable operators and tasks to be refined later into sub-workflows. This new representation helps users to structure and handle workflows, as it constrains the number of operators that need to be considered. Finally, workflows can be grouped in templates which foster re-use further simplifying DM workflow construction.
Other Identification Number 1434
PDF File Download from ZORA
Export BibTeX