Name
Abstract | ||
|---|---|---|
Today in many domains there are very limited explicit ontologies established for building information systems. The information systems have only schemas for their information repositories which to some extent imply the semantics of the information. Traditional ontology-driven semantic integration approaches cannot be directly applied in integrating these information systems. In our work we use the schemas and data instances of the information repositories to discover semantic correspondences between the schema elements and build a domain ontological view. We apply the hierarchical clustering technique on the data instances and use the clusters in the further analysis to reduce the cost of processing a large amount of data. The matching of schema elements is based on the probability distribution of the data instances. The preliminary results have demonstrated the effectiveness of this approach. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CSCWD.2009.4968082 | CSCWD |
Keywords | DocType | Citations |
schema element,instance-based domain ontological view,semantic correspondence,information system,hierarchical clustering technique,domain ontological view,large amount,information repository,data instance,explicit ontology,traditional ontology-driven semantic integration,ontologies,probability distribution,couplings,computer aided manufacturing,probability density function,probability,information systems,semantic integration,clustering,collaboration,hierarchical clustering,kernel,schema,owl | Conference | 0 |
PageRank | References | Authors |
0.34 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yunjiao Xue | 1 | 63 | 9.07 |
| Hamada Ghenniwa | 2 | 340 | 45.30 |
| Weiming Shen | 3 | 3407 | 343.73 |