Marc Ehrig, Jérôme Euzenat, Relaxed precision and recall for ontology matching, in: Benjamin Ashpole, Jérôme Euzenat, Marc Ehrig, Heiner Stuckenschmidt (eds), Proc. K-Cap workshop on integrating ontology, Banff (CA), pp25-32, 2005
In order to evaluate the performance of ontology matching algorithms it is necessary to confront them with test ontologies and to compare the results. The most prominent criteria are precision and recall originating from information retrieval. However, it can happen that an alignment be very close to the expected result and another quite remote from it, and they both share the same precision and recall. This is due to the inability of precision and recall to measure the closeness of the results. To overcome this problem, we present a framework for generalizing precision and recall. This framework is instantiated by three different measures and we show in a motivating example that the proposed measures are prone to solve the problem of rigidity of classical precision and recall.
In the definition of recall-oriented proximity (Table 7, 'relaxed recall based on relation', §4.4.2), the minimum (0) and maximum values (1) are inverted. This problem was independently identified by Jérôme David and Daniel Faria.