Search-space reduction for post-matching correspondence provisioning

If users participate in ontology matching, the goal always is to minimize the amount of necessary interactions while maximizing the gains in alignment quality [2]. Interaction can either happen pre-matching (selection of matching systems or parameter tuning), during the matching process (judging intermediate results or providing sample correspondences), or post-matching (detecting incorrect correspondences and providing missing ones). In this paper, we evaluate an approach that aims to reduce post matching interactions by exploiting concept proximity within ontologies. An initial analysis of reference alignments available for OAEI revealed that, if a correspondence for one element (class or property) of an ontology exists, the probability that a correspondence also exists for a closely connected element is higher than for unconnected elements. Based on this finding, we extracted the closeness criteria depicted in Figure 1. For evaluation, we applied the criteria on candidate alignments that were created by top-performing systems of OAEI 2014 for the anatomy, library, and conference tracks. For each criterion, we determined which elements it would add to the task set, i.e., the selection of ontology elements a user should provide correspondences for. Based on these task sets (UT ) we calculated the expected number of interactions (IE) it would on average take to provide all included correspondences (IC), if elements were presented to the user at random. To assess whether our selection technique is viable, we further compared this value to the amount of interactions it would take users on average to provide the same amount of missing correspondences, if tasks were randomly selected from the entirety of elements that are not included in correspondences after initial, automatic matching.