Reasoning in description logics
Principles of knowledge representation
Generic Schema Matching with Cupid
Proceedings of the 27th International Conference on Very Large Data Bases
Facilitating the Exchange of Explicit Knowledge through Ontology Mappings
Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference
PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
The Chimaera Ontology Environment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A system for principled matchmaking in an electronic marketplace
WWW '03 Proceedings of the 12th international conference on World Wide Web
Ontology mapping: the state of the art
The Knowledge Engineering Review
The Knowledge Engineering Review
Semantic integration: a survey of ontology-based approaches
ACM SIGMOD Record
A pragmatic approach to semantic repositories benchmarking
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
| Hi-index | 0.00 |
Internet-based e-commerce provides a high level of flexibility and openness though presenting many drawbacks due to the heterogeneity of the exchanged information. Ontologies are a key technology to solve many of the problems of e-commerce, in fact many companies use ontologies as a method of exchanging meaning between different agents. As ontology usage becomes more prevalent, the need for ontology reconciliation increases. In fact, ontology mapping methods can contribute to solve the problem of knowledge communication and interchange. In this paper we present an automatic method for ontology mapping. The method is made up of two phases: a lexical-semantic analysis based on the WordNet thesaurus and a structural analysis based on a matching algorithm that finds semantic mappings between two ontologies expressed in Attributive Language with Number description ($\mathcal{ALN}$) Description logic. The mapped ontologies describe the same conceptualization through a set of rules that join related concepts. We deployed the proposed approach in a prototype system that currently is employed for large scale experiments. A simple experiment with a case study domain has shown a good correspondence with human mapping manually conducted and the system provided results.