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Communication Dans Un Congrès Année : 2019

POMap++ results for OAEI 2019: fully automated machine learning approach for ontology matching

Résumé

POMap++ is a novel ontology matching system based on a machine learning approach. This year is the second participation of POMap++ in the Ontology Alignment Evaluation Initiative (OAEI). POMap++ follows a fully automated local matching learning approach that breaks down a large ontology matching task into a set of independent local sub-matching tasks. This approach integrates a novel partitioning algorithm as well as a set of matching learning techniques. POMap++ provides an automated local matching learning for the biomedical tracks. In this paper, we present POMap++ as well as the obtained results for the Ontology Alignment Evaluation Initiative of 2019.
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Dates et versions

hal-02942337 , version 1 (17-09-2020)

Identifiants

  • HAL Id : hal-02942337 , version 1
  • OATAO : 26321

Citer

Amir Laadhar, Faïza Ghozzi, Imen Megdiche, Franck Ravat, Olivier Teste, et al.. POMap++ results for OAEI 2019: fully automated machine learning approach for ontology matching. 14th International Workshop on Ontology Matching co-located with the International Semantic Web Conference (OM@ISWC 2019), Oct 2019, Auckland, New Zealand. pp.169-174. ⟨hal-02942337⟩
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