- Tytuł:
- Introducing artificial neural network in ontologies alignment process
- Autorzy:
-
Djeddi, W. E.
Khadir, M. T. - Powiązania:
- https://bibliotekanauki.pl/articles/206314.pdf
- Data publikacji:
- 2012
- Wydawca:
- Polska Akademia Nauk. Instytut Badań Systemowych PAN
- Tematy:
-
artificial neural network
training
ontology alignment
WordNet
XMap++ - Opis:
- Ontology alignment uses different similaritymeasures of different categories such as string, linguistic, and structural based similarity measures to understand ontologies’ semantics. A weights vector must, therefore, be assigned to these similarity measures, if a more accurate and meaningful alignment result is favored. Combining multiple measures into a single similarity metric has been traditionally solved using weights determined manually by an expert, Or calculated through general methods (e.g. average or sigmoid function) that do not provide optimal results. In this paper, we propose an artificial neural network algorithm to ascertain how to Combie multiple similarity measures into a single aggregated metric with the final aim of improving the ontology alignment quality. XMap++ is applied to benchmark tests at OAEI campaign 2010. Results show that neural network boosts the performance in most cases, and that the proposed novel approach is competitive with top-ranked system.
- Źródło:
-
Control and Cybernetics; 2012, 41, 4; 743-759
0324-8569 - Pojawia się w:
- Control and Cybernetics
- Dostawca treści:
- Biblioteka Nauki
Artykuł