Name
Abstract | ||
|---|---|---|
Currently, schema integration frameworks use approaches like rule-based, machine learning, etc. This paper presents an ontology-based wrapper-mediator framework that uses both the rule-based and machine learning strategies at the same time. The proposed framework uses global and local ontologies for resolving syntactic and semantic heterogeneity, and XML for interoperability. The concepts in the candidate schemas are merged on the basis of the similarity coefficient, which is calculated using the defined rules and the prior mappings stored in the case-base. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/s11390-005-0788-4 | J. Comput. Sci. Technol. |
Keywords | Field | DocType |
semi-automatic schema integration,candidate schema,proposed framework,schema integration framework,machine learning,similarity coefficient,prior mapping,local ontology,ontology-based wrapper-mediator framework,ontology-based framework,semantic heterogeneity,rule based,database integration | Data integration,Ontology (information science),Ontology,Ontology-based data integration,XML,Information retrieval,Computer science,Interoperability,Database schema,Semantic heterogeneity | Journal |
Volume | Issue | ISSN |
20 | 6 | 1860-4749 |
Citations | PageRank | References |
6 | 0.55 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zille Huma | 1 | 28 | 3.13 |
| Muhammad Jaffar-Ur Rehman | 2 | 96 | 4.54 |
| Nadeem Iftikhar | 3 | 80 | 11.50 |