Balancing Brave and Cautious Query Strategies in Ontology Debugging
Sequential ontology debugging is aimed at the efficient discrimination between diagnoses, i.e. sets of axioms which must be altered or deleted from the ontology to restore onsistency. By querying additional information the number of possible diagnoses can be radually reduced. The selection of the best queries is crucial for minimizing diagnosis costs. If prior fault probabilities (FPs) are
available, the best results are achieved by entropy based query selection. Given that FPs are only weakly justified, however, this strategy bravely suggests suboptimal queries although more cautious strategies should be followed. In such a case, it is more efficient to follow a no-risk strategy which prefers queries that eliminate 50% of diagnoses ndependently of any FPs. However, choosing the
appropriate strategy in advance is impossible because the quality of given priors cannot be assessed before additional information is queried. We propose a method which combines advantages of both approaches. On the one hand, the method takes into account available meta inform ation in terms of FPs and the
user’s confidence in these. On the other hand, the method can cope with weakly justified FPs by limiting the risk of suboptimal query selections based on the user’s confidence in the FPs. The readiness to take risk is adapted depending on the outcome of previous queries. Our comprehensive evaluation shows that the
proposed debugging method significantly reduces the number of queries compared to both the entropy based and the no-risk strategy for any choice of FPs.
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