YAM: a Schema Matcher Factory

Fabien Duchateau (1) , Remi Coletta (2) , Zohra Bellahsene (2) , Renée J. Miller (3)

1 LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
2 ZENITH - Scientific Data Management
3 DCS - Department of Computer Science [University of Toronto]

In this paper, we present YAM, a schema matcher factory. YAM (Yet Another Matcher) is not (yet) another schema matching system as it enables the generation of a la carte schema matchers according to user requirements. These re- quirements include a preference for recall or precision, a training data set (schemas already matched) and provided expert correspondences. YAM uses a knowledge base that includes a (possibly large) set of similarity measures and classifiers. Based on the user requirements, YAM learns how to best apply these tools (similarity measures and clas- sifiers) in concert to achieve the best matching quality. In our demonstration, we will let users apply YAM to build the best schema matcher for different user requirements.

Mots clés: Schema matching; data integration; matcher factory; machine learning; XML schemas; YAM; Yet Another Matcher; demo

Domaines: Base de données [cs.DB]; Apprentissage [cs.LG]

Fabien Duchateau, Remi Coletta, Zohra Bellahsene, Renée J. Miller. YAM: a Schema Matcher Factory. RR-09018, 2009. ⟨lirmm-00399184⟩