Reconciling schemas of disparate data sources: a machine-learning approach
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Generic Schema Matching with Cupid
Proceedings of the 27th International Conference on Very Large Data Bases
Semantic integration: a survey of ontology-based approaches
ACM SIGMOD Record
Schema and ontology matching with COMA++
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Automatic ontology matching using application semantics
AI Magazine - Special issue on semantic integration
Putting context into schema matching
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
GORDIAN: efficient and scalable discovery of composite keys
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Why is schema matching tough and what can we do about it?
ACM SIGMOD Record
COMA: a system for flexible combination of schema matching approaches
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
BioFlow: A Web-Based Declarative Workflow Language for Life Sciences
SERVICES '08 Proceedings of the 2008 IEEE Congress on Services - Part I
An iterative algorithm for ontology mapping capable of using training data
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
On the cardinality of schema matching
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems
Soundness of schema matching methods
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
Ontology mapping: a way out of the medical tower of babel?
AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine
DILS '09 Proceedings of the 6th International Workshop on Data Integration in the Life Sciences
On-the-Fly Integration and Ad Hoc Querying of Life Sciences Databases Using LifeDB
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Ontology guided autonomous label assignment in wrapper induced tables with missing column names
IRI'09 Proceedings of the 10th IEEE international conference on Information Reuse & Integration
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Traditional schema matchers use a set of distinct simple matchers and use a composition function to combine the individual scores using an arbitrary order of matcher application leading to non-intuitive scores, produce improper matches, and wasteful and counterproductive computation, especially when no consideration is given to the properties of the individual matchers and the context of the application. In this paper, we propose a new method for schema matching in which wasteful computation is avoided by a prudent, and objective selection and ordering of a subset of useful matchers. This method thus has the potential to improve the matching efficiency and accuracy of many popular ontology generation engines. Such efficiency and quality assurance are imperative in autonomous systems because users rarely have a chance to validate the processing accuracy until the computation is complete. Experimental results to support the claim that such an approach monotonically improves the matching score at successive application of the matchers are also provided.