On Expert Behaviors and Question Types for Efficient Query-Based Ontology Fault Localization
January 16, 2020 Β· Declared Dead Β· π arXiv.org
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Authors
Patrick Rodler
arXiv ID
2001.05952
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.HC,
cs.LO,
cs.PF
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
We challenge existing query-based ontology fault localization methods wrt. assumptions they make, criteria they optimize, and interaction means they use. We find that their efficiency depends largely on the behavior of the interacting expert, that performed calculations can be inefficient or imprecise, and that used optimization criteria are often not fully realistic. As a remedy, we suggest a novel (and simpler) interaction approach which overcomes all identified problems and, in comprehensive experiments on faulty real-world ontologies, enables a successful fault localization while requiring fewer expert interactions in 66 % of the cases, and always at least 80 % less expert waiting time, compared to existing methods.
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