Schema matching is the process of developing semantic matches between two or more schemas. The purpose of schema matching is generally either to merge two or more databases, or to enable queries on multiple, heterogeneous databases to be formulated on a single schema (Doan and Halevy 2005). This paper develops a taxonomy of schema matching approaches, classifying them as being based on a combination schema matching technique and the type of data used by those techniques. Schema matching techniques are categorized as being based on rules, learning, or ontology, and the type of data used is categorized as being based on schema elements or instance data. This taxonomy is an extension to previous work, and significant current research efforts a...
This chapter presents the generic schema match system, COmbination MAtch (COMA), which provides an e...
Schema management is a basic problem in many database application domains such as data integration s...
Schema matching aims at identifying semantic correspondences between elements of two schemas, e.g., ...
Schema matching is the process of developing semantic matches between two or more schemas. The purpo...
Schema/ontology matching is a critical problem in many application domains, such as, Semantic Web, s...
Schema matching is a critical step in many applications, such as data warehouse loading, Online Anal...
Schema matching is a basic problem in many database application domains, such as data integration, E...
Schema matching is considered as one of the essential phases of data integration in database systems...
shvaiko2005aInternational audienceSchema and ontology matching is a critical problem in many applica...
Schema matching is critical problem within many applications to integration of data/information, to ...
Schema and ontology matching is a critical problem in many application domains, such as semantic web...
Schema matching is a basic problem in many database application domains, such as data integration. T...
Schema matching is a basic problem in many database application domains, such as data integration. T...
Ontology matching is an important task when data from multiple data sources is integrated. Problems ...
This chapter presents the generic schema match system, COmbination MAtch (COMA), which provides an e...
This chapter presents the generic schema match system, COmbination MAtch (COMA), which provides an e...
Schema management is a basic problem in many database application domains such as data integration s...
Schema matching aims at identifying semantic correspondences between elements of two schemas, e.g., ...
Schema matching is the process of developing semantic matches between two or more schemas. The purpo...
Schema/ontology matching is a critical problem in many application domains, such as, Semantic Web, s...
Schema matching is a critical step in many applications, such as data warehouse loading, Online Anal...
Schema matching is a basic problem in many database application domains, such as data integration, E...
Schema matching is considered as one of the essential phases of data integration in database systems...
shvaiko2005aInternational audienceSchema and ontology matching is a critical problem in many applica...
Schema matching is critical problem within many applications to integration of data/information, to ...
Schema and ontology matching is a critical problem in many application domains, such as semantic web...
Schema matching is a basic problem in many database application domains, such as data integration. T...
Schema matching is a basic problem in many database application domains, such as data integration. T...
Ontology matching is an important task when data from multiple data sources is integrated. Problems ...
This chapter presents the generic schema match system, COmbination MAtch (COMA), which provides an e...
This chapter presents the generic schema match system, COmbination MAtch (COMA), which provides an e...
Schema management is a basic problem in many database application domains such as data integration s...
Schema matching aims at identifying semantic correspondences between elements of two schemas, e.g., ...