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Acta Informatica
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Measuring semantic similarity between Gene Ontology terms
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PERCOM '08 Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Semantic matching based on enterprise ontologies
OTM'07 Proceedings of the 2007 OTM Confederated international conference on On the move to meaningful internet systems: CoopIS, DOA, ODBASE, GADA, and IS - Volume Part I
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Reasoning by analogy in the generation of domain acceptable ontology refinements
EKAW'10 Proceedings of the 17th international conference on Knowledge engineering and management by the masses
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Ontology-based relevance assessment of documents is an important task. When viewing this in a business context, approaches are commonly based on the use of one ontology describing the enterprise. A more specific problem is then how to assess the relevance of a set of ontology concepts with respect to a user profile expressed within the same ontology. Semantic similarity measures have been widely used and described in literature, but few experiments have been performed to show the benefits and drawbacks of certain measures. In this paper we describe how a set of measures have been combined, tested, and evaluated. The evaluation was performed through a rank correlation coefficient comparing the measured results with a manually constructed "gold standard". Conclusions are that certain combinations of measures seem less suitable for solving this type of problem. On the other hand a set of combinations perform quite well, although the detailed performance of most combined measures seem to depend heavily on the structure of the ontology used.