Large data integration projects must often cope with undocumented data sources. Schema discovery aims at automatically finding structures in such cases. An important class of relationships between attributes that can be detected automatically are inclusion dependencies (IND), which provide an excellent basis for guessing foreign key constraints. INDs can be discovered by comparing the sets of distinct values of pairs of attributes. In thi
A two-step optimization strategy for relational schemas that contains a class of inclusion dependenc...
Relational database schemas must be semantically enriched to reflect knowledge about the data, as ne...
This paper introduces a class of conditional inclusion dependencies (CINDs), which extends tradition...
Data sources for data integration often come with spurious schema definitions such as undefined fore...
Large data integration projects must often cope with undocumented data sources. Schema discovery aim...
In large integration projects one is often confronted with poorly documented databases. One possibil...
International audienceForeign keys form one of the most fundamental constraints for relational datab...
Determining relationships such as functional or inclusion dependencies within and across databases i...
Data integration in the life sciences is currently implemented by very costly manually curated proje...
International audienceForeign keys form one of the most fundamental constraints for relational datab...
International audienceInclusion dependencies together with functional dependencies form the most imp...
International audienceDeclarative pattern mining implies to define common frameworks and atomic oper...
Most data integration applications require a matching between the schemas of the respective data set...
National audienceInclusion dependencies together with functional dependencies form the most fundamen...
Relational database schemas must be semantically enriched to reflect knowledge about the data, as ne...
A two-step optimization strategy for relational schemas that contains a class of inclusion dependenc...
Relational database schemas must be semantically enriched to reflect knowledge about the data, as ne...
This paper introduces a class of conditional inclusion dependencies (CINDs), which extends tradition...
Data sources for data integration often come with spurious schema definitions such as undefined fore...
Large data integration projects must often cope with undocumented data sources. Schema discovery aim...
In large integration projects one is often confronted with poorly documented databases. One possibil...
International audienceForeign keys form one of the most fundamental constraints for relational datab...
Determining relationships such as functional or inclusion dependencies within and across databases i...
Data integration in the life sciences is currently implemented by very costly manually curated proje...
International audienceForeign keys form one of the most fundamental constraints for relational datab...
International audienceInclusion dependencies together with functional dependencies form the most imp...
International audienceDeclarative pattern mining implies to define common frameworks and atomic oper...
Most data integration applications require a matching between the schemas of the respective data set...
National audienceInclusion dependencies together with functional dependencies form the most fundamen...
Relational database schemas must be semantically enriched to reflect knowledge about the data, as ne...
A two-step optimization strategy for relational schemas that contains a class of inclusion dependenc...
Relational database schemas must be semantically enriched to reflect knowledge about the data, as ne...
This paper introduces a class of conditional inclusion dependencies (CINDs), which extends tradition...