In this paper we present a new method of semantic schema integration, based on uncertain semantic mappings. The purpose of semantic schema integration is to produce a unified representation of multiple data sources. First, schema matching is performed to identify the semantic mappings between the schema objects. Then, an integrated schema is produced during the schema merging process based on the identified mappings. If all semantic mappings are known, schema merging can be performed (semi-)automatically
In this article we argue for the lack of formal foundations for ontology-based semantic alignment. W...
Schema integration is the process of consolidating several source schemas to generate a unified view...
Abstract. One of the key challenges in the development of open semantic-based systems is enabling th...
This paper addresses the problem of handling semantic heterogeneity during database schema integrati...
Contrary to existing heterogeneous data integration systems which need to be fully integrated before...
This paper reports our first set of results on managing uncertainty in data integration. We posit th...
none4Lecture Notes in Computer SciencenoneN. Rizopoulos; M. Magnani; P. McBrien; D. MontesiN. Rizopo...
In a multidatabase system, schematic conflicts between two objects are usually of interest only when...
Schema and ontology matching play an important part in the field of data integration and semantic we...
Mapping ontologies with high precision on the Semantic Web is a challenging problem that needs to be...
none4noneN. Rizopoulos; M. Magnani; P. McBrien; D. MontesiN. Rizopoulos; M. Magnani; P. McBrien; D. ...
Nowadays many application require information from di-verse data sources, in which related data may ...
AbstractA data integration system provides the user with a unified view, called global schema, of th...
In a multi-database system, schematic conflicts between two objects are usually of interest only whe...
Managing uncertainty on the Semantic Web can potentially improve the ontology mapping precision whic...
In this article we argue for the lack of formal foundations for ontology-based semantic alignment. W...
Schema integration is the process of consolidating several source schemas to generate a unified view...
Abstract. One of the key challenges in the development of open semantic-based systems is enabling th...
This paper addresses the problem of handling semantic heterogeneity during database schema integrati...
Contrary to existing heterogeneous data integration systems which need to be fully integrated before...
This paper reports our first set of results on managing uncertainty in data integration. We posit th...
none4Lecture Notes in Computer SciencenoneN. Rizopoulos; M. Magnani; P. McBrien; D. MontesiN. Rizopo...
In a multidatabase system, schematic conflicts between two objects are usually of interest only when...
Schema and ontology matching play an important part in the field of data integration and semantic we...
Mapping ontologies with high precision on the Semantic Web is a challenging problem that needs to be...
none4noneN. Rizopoulos; M. Magnani; P. McBrien; D. MontesiN. Rizopoulos; M. Magnani; P. McBrien; D. ...
Nowadays many application require information from di-verse data sources, in which related data may ...
AbstractA data integration system provides the user with a unified view, called global schema, of th...
In a multi-database system, schematic conflicts between two objects are usually of interest only whe...
Managing uncertainty on the Semantic Web can potentially improve the ontology mapping precision whic...
In this article we argue for the lack of formal foundations for ontology-based semantic alignment. W...
Schema integration is the process of consolidating several source schemas to generate a unified view...
Abstract. One of the key challenges in the development of open semantic-based systems is enabling th...