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Accuracy +
Use four ontologies from OAEI 2010 benchmark, calculating the classification time for these ontologies. +
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In this paper, we present LogMap, a highly …
In this paper, we present LogMap, a highly scalable ontology matching system with built-in reasoning and diagnosis capabilities. To the best of our knowledge, LogMap is the only matching system that can deal with semantically rich ontologies containing tens (and even hun-dreds) of thousands of classes. In contrast to most existing tools, LogMap also implements algorithms for on the fly unsatisability detection and repair. Our experiments with the ontologies NCI, FMA and SNOMEDCT confirm that our system can efficiently match even the largest existing bio-medical ontologies. Furthermore, LogMap is able to produce a `clean' set of output mappings in many cases, in the sense that the ontology obtained by integrating LogMap's output mappings with the input ontologies is consistent and does not contain unsatisable classes.
and does not contain unsatisable classes. +
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In this paper, we have presented LogMap, a …
In this paper, we have presented LogMap, a highly scalable ontology matching tool with built-in reasoning and diagnosis capabilities. LogMap's features and scalability behaviour make it well-suited for matching large-scale ontologies. LogMap, however, is still an early-stage prototype and there is plenty of room for improvement.
d there is plenty of room for improvement. +
We are currently working on further optimizations, and in the near future, we are planning to integrate LogMap with a Protege-based front-end, such as the one implemented in our tool ContentMap. +
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Creation date
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13:29:28, 27 June 2018 +
Last editor is
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Modification date
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11:16:13, 12 July 2018 +
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