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Applying Optimal Stopping Theory to Improve the Performance of Ontology Refinement Methods

Weichselbraun, Albert and Wohlgenannt, Gerhard and Scharl, Arno (2011) Applying Optimal Stopping Theory to Improve the Performance of Ontology Refinement Methods. In: Proceedings of the 44th Hawaii International Conference on System Sciences (HICSS-44), January 4-7, 2011, Maui, Hawaii.

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Official URL: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arn...

Abstract

Recent research shows the potential of utilizing data collected through Web 2.0 applications to capture domain evolution. Relying on external data sources, however, often introduces delays due to the time spent retrieving data from these sources. The method introduced in this paper streamlines the data acquisition process by applying optimal stopping theory. An extensive evaluation demonstrates how such an optimization improves the processing speed of an ontology refinement component which uses Delicious to refine ontologies constructed from unstructured textual data while having no significant impact on the quality of the refinement process. Domain experts compare the results retrieved from optimal stopping with data obtained from standardized techniques to assess the effect of optimal stopping on data quality and the created domain ontology.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:ontology refinement, optimal stopping, social sources
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
ID Code:31
Deposited By: Dr Albert Weichselbraun
Deposited On:29 Sep 2011 19:16
Last Modified:29 Sep 2011 19:16

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