Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
Learning in FOL with a similarity measure
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Semantic Similarity, Ontologies and the Portuguese Language: A Close Look at the subject
PROPOR '08 Proceedings of the 8th international conference on Computational Processing of the Portuguese Language
ASWC '09 Proceedings of the 4th Asian Conference on The Semantic Web
UFOme: An ontology mapping system with strategy prediction capabilities
Data & Knowledge Engineering
Query distributed ontology over grid environment
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part III
Ontology matching using vector space
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
How to search in MPEG-7 based semantic descriptions: an evaluation of metrics
Multimedia Tools and Applications
Linked open data to support content-based recommender systems
Proceedings of the 8th International Conference on Semantic Systems
A conceptual graph based approach for mappings among multiple fuzzy ontologies
Journal of Web Engineering
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Ontology alignment (or matching) is the operation that takes two ontologies and produces a set of semantic correspondences (usually semantic similarities) between some elements of one of them and some elements of the other. A rigorous, efficient and scalable similarity measure is a pre-requisite of an ontology alignment process. This paper presents a semantic similarity measure based on a matrix represention of nodes from an RDF labelled directed graph. An entity is described with respect to how it relates to other entities using N-dimensional vectors, being N the number of selected external predicates. We adapt a known graph matching algorithm when applying this idea to the alignment of two ontologies. We have successfully tested the model with the public testcases of the Ontology Alignment Evaluation Initiative 2005.