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Auto-experimentation of KDD workflows based on ontological planning

Serban, F (2010). Auto-experimentation of KDD workflows based on ontological planning. In: The 9th International Semantic Web Conference (ISWC 2010), Doctoral Consortium, Shanghai, China, 7 November 2010 - 11 November 2010, 313-320.

Abstract

One of the problems of Knowledge Discovery in Databases (KDD) is the lack of user support for solving KDD problems. Current Data Mining (DM) systems enable the user to manually design workflows but this becomes difficult when there are too many operators to choose from or the workflow's size is too large. Therefore we propose to use auto-experimentation based on ontological planning to provide the users with automatic generated workflows as well as rankings for workflows based on several criteria (execution time, accuracy, etc.). Moreover auto-experimentation will help to validate the generated workflows and to prune and reduce their number. Furthermore we will use mixed-initiative planning to allow the users to set parameters and criteria to limit the planning search space as well as to guide the planner towards better workflows.

Additional indexing

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
Scopus Subject Areas:Physical Sciences > Theoretical Computer Science
Physical Sciences > General Computer Science
Scope:Discipline-based scholarship (basic research)
Language:English
Event End Date:11 November 2010
Deposited On:24 Feb 2011 15:11
Last Modified:06 Mar 2024 13:57
OA Status:Hybrid
Publisher DOI:https://doi.org/10.1007/978-3-642-17749-1_22
Other Identification Number:1461; merlin-id:5

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