Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Learning to match ontologies on the Semantic Web
The VLDB Journal — The International Journal on Very Large Data Bases
Ontology mapping: the state of the art
The Knowledge Engineering Review
Semantic integration: a survey of ontology-based approaches
ACM SIGMOD Record
Constructing virtual documents for ontology matching
Proceedings of the 15th international conference on World Wide Web
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Ontology Alignment: Bridging the Semantic Gap (Semantic Web and Beyond)
Ontology Alignment: Bridging the Semantic Gap (Semantic Web and Beyond)
A Profile Propagation and Information Retrieval Based Ontology Mapping Approach
SKG '07 Proceedings of the Third International Conference on Semantics, Knowledge and Grid
An adaptive ontology mapping approach with neural network based constraint satisfaction
Web Semantics: Science, Services and Agents on the World Wide Web
Design of a P2P content recommendation system using affinity networks
Computer Communications
SIGMa: simple greedy matching for aligning large knowledge bases
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
DocCloud: A document recommender system on cloud computing with plausible deniability
Information Sciences: an International Journal
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Ontology mapping is to find semantic correspondences between similar elements of different ontologies. It is critical to achieve semantic interoperability in the WWW. This paper proposes a new generic and scalable ontology mapping approach based on propagation theory, information retrieval technique and artificial intelligence model. The approach utilizes both linguistic and structural information, measures the similarity of different elements of ontologies in a vector space model, and deals with constraints using the interactive activation network. The results of pilot study, the PRIOR, are promising and scalable.