Entity Identification in Database Integration
Proceedings of the Ninth International Conference on Data Engineering
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Ontology Matching
Polygon-Based Similarity Aggregation for Ontology Matching
ISPA '07 Proceedings of the SSDSN, UPWN, WISH, SGC, ParDMCom, HiPCoMB, and IST-AWSN international workshops held at ISPA 2007 on Frontiers of High Performance Computing and Networking
A survey of schema-based matching approaches
Journal on Data Semantics IV
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Ontologies, as essential elements of the semantic web, have been developed for various purposes and in many different domains. Many ontologies are quite extensive and sophisticated, capturing essential knowledge in a domain. However, ontology users or engineers do not only use their own ontologies, but also want to integrate or adapt other ontologies, or even apply multiple ontologies to solve a problem. As ontologies themselves can be heterogenous, it is necessary to find ways to integrate various ontologies and enable cooperation between them. Ontology matching for finding similar parts in the source ontologies or finding translation rules between ontologies is an important first step. Different strategies (e.g., string similarity, synonyms, structure similarity and based on instances) for determining similarity between entities are used in current ontology matching systems.A lot of existing research work in automatic matching does not sufficiently take into account the user's requirements in the ontology matching process. In real world, the user's or domain expert's requirements play an important role. In this paper, we propose to integrate user-based constraint strategy in ontology matching. The proposed approach includes excluding rules, dominant key and extended key definition and extended key aggregation.