Information for "AgreementMaker: Efficient Matching for Large Real-World Schemas and Ontologies"

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Display titleAgreementMaker: Efficient Matching for Large Real-World Schemas and Ontologies
Default sort keyAgreementMaker: Efficient Matching for Large Real-World Schemas and Ontologies
Page length (in bytes)3,065
Page ID36167
Page content languageen - English
Page content modelwikitext
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Counted as a content pageYes

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Page creatorSaid (talk | contribs)
Date of page creation14:12, 27 June 2018
Latest editorSaid (talk | contribs)
Date of latest edit23:24, 11 July 2018
Total number of edits7
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 seriesVLDB +
Has BenchmarkOAEI 2012 +
Has ChallengesNo data available now. +
Has DataCatalouge- +
Has DescriptionNo data available now. +
Has DimensionsAccuracy +
Has DocumentationURLhttp://No data available now. +
Has Downloadpagehttps://github.com/agreementmaker/agreementmaker +
Has EvaluationPerformance Evaluation +
Has EvaluationMethodCompare the mappings found by the system between the two ontologies with a reference matching or “gold standard,” which is a set of correct and complete mappings as built by domain experts. +
Has ExperimentSetupNo data available now. +
Has GUIYes +
Has HypothesisNo data available now. +
Has ImplementationAgreementMaker +
Has InfoRepresentationXML, RDF, OWL, or N3 +
Has LimitationsNo data available now. +
Has NegativeAspectsNo data available now. +
Has PositiveAspectsNo data available now. +
Has RequirementsNo data available now. +
Has ResultsExperiments have shown that our quality measure is usually effective in defining weights for the LWC matcher. +
Has SubproblemNo data available now. +
Has Version0.23 +
Has abstractWe present the AgreementMaker system for m
We present the AgreementMaker system for matching real-world schemas and ontologies, which may consist of hundreds or even thousands of concepts. The end users of the system are sophisticated domain experts whose needs have driven the design and implementation of the system: they require a responsive, powerful, and extensible framework to perform, evaluate, and compare matching methods. The system comprises a wide range of matching methods addressing different levels of granularity of the components being matched (conceptual vs. structural), the amount of user intervention that they require (manual vs. automatic), their usage (stand-alone vs. composed), and the types of components to consider (schema only or schema and instances). Performance measurements (recall, precision, and runtime) are supported by the system, along with the weighted combination of the results provided by those methods. The AgreementMaker has been used and tested in practical applications and in the Ontology Alignment Evaluation Initiative (OAEI) competition. We report here on some of its most advanced features, including its extensible architecture that facilitates the integration and performance tuning of a variety of matching methods, its capability to evaluate, compare, and combine matching results, and its user interfaces with a control panel that drives all the matching methods and evaluation strategies.
atching methods and evaluation strategies. +
Has approachNo data available now. +
Has authorsIsabel F. Cruz +, Flavio Palandri Antonelli + and Cosmin Stroe +
Has conclusionNo data available now. +
Has future workNo data available now. +
Has motivationNo data available now. +
Has platformNo data available now. +
Has problemLink Discovery +
Has relatedProblemNo data available now. +
Has subjectOntology Alignment +
Has vendorNo data available now. +
Has year2009 +
ImplementedIn ProgLangJava +
Proposes AlgorithmNo data available now. +
RunsOn OSNo data available now. +
TitleAgreementMaker: Efficient Matching for Large Real-World Schemas and Ontologies +
Uses FrameworkNo data available now. +
Uses MethodologyNo data available now. +
Uses ToolboxNo data available now. +