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Designing KDD-Workflows via HTN-Planning for Intelligent Discovery Assistance


Kietz, Jörg-Uwe; Serban, Floarea; Bernstein, Abraham; Fischer, Simon (2012). Designing KDD-Workflows via HTN-Planning for Intelligent Discovery Assistance. In: Planning to Learn 2012, Workshop at ECAI 2012, Montpellier, France, 28 August 2012 - 28 August 2012.

Abstract

Knowledge Discovery in Databases (KDD) has evolved a lot during the last years and reached a mature stage offering plenty of operators to solve complex data analysis tasks. However, the user support for building workflows has not progressed accordingly. The large number of operators currently available in KDD systems makes it difficult for users to successfully analyze data. In addition, the cor- rectness of workflows is not checked before execution. Hence, the execution of a workflow frequently stops with an error after several hours of runtime.This paper presents our tools, eProPlan and eIDA, which solve the above problems by supporting the whole life-cycle of (semi-) auto- matic workflow generation. Our modeling tool eProPlan allows to describe operators and build a task/method decomposition grammar to specify the desired workflows. Additionally, our Intelligent Dis- covery Assistant, eIDA, allows to place workflows into data mining (DM) tools or workflow engines for execution.

Abstract

Knowledge Discovery in Databases (KDD) has evolved a lot during the last years and reached a mature stage offering plenty of operators to solve complex data analysis tasks. However, the user support for building workflows has not progressed accordingly. The large number of operators currently available in KDD systems makes it difficult for users to successfully analyze data. In addition, the cor- rectness of workflows is not checked before execution. Hence, the execution of a workflow frequently stops with an error after several hours of runtime.This paper presents our tools, eProPlan and eIDA, which solve the above problems by supporting the whole life-cycle of (semi-) auto- matic workflow generation. Our modeling tool eProPlan allows to describe operators and build a task/method decomposition grammar to specify the desired workflows. Additionally, our Intelligent Dis- covery Assistant, eIDA, allows to place workflows into data mining (DM) tools or workflow engines for execution.

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Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:28 August 2012
Deposited On:07 Dec 2012 15:56
Last Modified:07 Dec 2017 16:49
Official URL:http://datamining.liacs.nl/planlearnpapers/planlearn2012_submission_3.pdf
Related URLs:http://datamining.liacs.nl/planlearn.html
Other Identification Number:merlin-id:7142

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