Information for "LogMap: Logic-based and Scalable Ontology Matching"

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Display titleLogMap: Logic-based and Scalable Ontology Matching
Default sort keyLogMap: Logic-based and Scalable Ontology Matching
Page length (in bytes)2,752
Page ID36170
Page content languageen - English
Page content modelwikitext
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Page creatorSaid (talk | contribs)
Date of page creation14:29, 27 June 2018
Latest editorSaid (talk | contribs)
Date of latest edit12:16, 12 July 2018
Total number of edits6
Total number of distinct authors1
Recent number of edits (within past 90 days)0
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Access APINo data available now. +
Event in seriesISWC +
Has BenchmarkOAEI 2010 +
Has ChallengesNo data available now. +
Has DataCatalouge- +
Has DescriptionNo data available now. +
Has DimensionsAccuracy +
Has DocumentationURLhttp://No data available now. +
Has Downloadpagehttp://www.cs.ox.ac.uk/isg/projects/LogMap/ +
Has EvaluationAccuracy Evaluation +
Has EvaluationMethodUse four ontologies from OAEI 2010 benchmark, calculating the classification time for these ontologies. +
Has ExperimentSetupNo data available now. +
Has GUINo +
Has HypothesisNo data available now. +
Has ImplementationLogMap +
Has InfoRepresentationNo data available now. +
Has LimitationsNo data available now. +
Has NegativeAspectsNo data available now. +
Has PositiveAspectsNo data available now. +
Has RequirementsNo data available now. +
Has ResultsNo data available now. +
Has SubproblemNo data available now. +
Has VersionNo data available now. +
Has abstractIn 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. +
Has approachNo data available now. +
Has authorsErnesto Jimenez-Ruiz + and Bernardo Cuenca Grau +
Has conclusionIn 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. +
Has future workWe 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. +
Has motivationNo data available now. +
Has platformNo data available now. +
Has problemLink Discovery +
Has relatedProblemNo data available now. +
Has subjectOntology Matching +
Has vendorNo data available now. +
Has year2011 +
ImplementedIn ProgLangJava +
Proposes AlgorithmNo data available now. +
RunsOn OSNo data available now. +
TitleLogMap: Logic-based and Scalable Ontology Matching +
Uses FrameworkNo data available now. +
Uses MethodologyNo data available now. +
Uses ToolboxNo data available now. +