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Applying Optimal Stopping Theory to Improve the Performance of Ontology Refinement Methods
2011
2011 44th Hawaii International Conference on System Sciences
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
doi:10.1109/hicss.2011.72
dblp:conf/hicss/WeichselbraunWS11
fatcat:ocqyifc3xvhzjfat3l7hsc4dky