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hal-03853319, version 1
Communication dans un congrès
MATCHING LARGE BIOMEDICAL ONTOLOGIES USING SYMBOLIC REGRESSION
Jorge Martinez-Gil 1 Shaoyi Yin 2 Josef Küng 3 Franck Morvan 2 Détails
1 SCCH - Software Competence Center Hagenberg
2 IRIT-PYRAMIDE - Optimisation Dynamique de Requêtes Réparties à grande échelle
IRIT - Institut de recherche en informatique de Toulouse
3 JKU - Johannes Kepler Universität Linz
> Jorge Martinez-Gil 1
> Auteur
> PersonId : 17728
> IdHAL : martinez-gil-jorgeORCID : 0000-0002-5730-7965IdRef : 253122732
> Shaoyi Yin 2
> Auteur
> PersonId : 184832
> IdHAL : shaoyi-yinORCID : 0000-0002-5335-2443IdRef : 15327400X
> Josef Küng 3
> Auteur
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> Franck Morvan 2
> Auteur
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> IdHAL : franck-morvanIdRef : 034867406
1 SCCH - Software Competence Center Hagenberg (Softwarepark 21 A-4232 Hagenberg
Austria - Autriche) StructId : 46694
* JKU - Johannes Kepler Universität Linz (Altenberger Straße 69, 4040 Linz -
Autriche) StructId : 300879
2 IRIT-PYRAMIDE - Optimisation Dynamique de Requêtes Réparties à grande échelle
(Institut de recherche en informatique de Toulouse - IRIT 118 Route de Narbonne
31062 Toulouse Cedex 9 - France) StructId : 1001829
* IRIT - Institut de recherche en informatique de Toulouse (118 Route de
Narbonne, F-31062 Toulouse Cedex 9 - France) StructId : 34499
* UT1 - Université Toulouse 1 Capitole (2 rue du Doyen-Gabriel-Marty - 31042
Toulouse Cedex 9 - France) StructId : 81148
* Université Fédérale Toulouse Midi-Pyrénées (41 Allée Jules Guesde, 31000
Toulouse - France) StructId : 443875
* UT2J - Université Toulouse - Jean Jaurès (5 allées Antonio Machado - 31058
Toulouse Cedex 9 - France) StructId : 116256
* UT3 - Université Toulouse III - Paul Sabatier (118 route de Narbonne -
31062 Toulouse - France) StructId : 217752
* Université Fédérale Toulouse Midi-Pyrénées (41 Allée Jules Guesde, 31000
Toulouse - France) StructId : 443875
* CNRS - Centre National de la Recherche Scientifique : UMR5505 (France)
StructId : 441569
* Toulouse INP - Institut National Polytechnique (Toulouse) (France) StructId
: 448187
* Université Fédérale Toulouse Midi-Pyrénées (41 Allée Jules Guesde, 31000
Toulouse - France) StructId : 443875
3 JKU - Johannes Kepler Universität Linz (Altenberger Straße 69, 4040 Linz -
Autriche) StructId : 300879
Masquer les détails
Abstract : The problem of ontology matching consists of finding the semantic
correspondences between two ontologies that, although belonging to the same
domain, have been developed separately. Matching methods are of great importance
since they allow us to find the pivot points from which an automatic data
integration process can be established. Unlike the most recent developments
based on deep learning, this study presents our research on the development of
new methods for ontology matching that are accurate and interpretable at the
same time. For this purpose, we rely on a symbolic regression model specifically
trained to find the mathematical expression that can solve the ground truth
accurately, with the possibility of being understood by a human operator and
forcing the processor to consume as little energy as possible. The experimental
evaluation results show that our approach seems to be promising.
Keywords : Ontology matching Ontology alignment Symbolic Regression Very Large
Ontologies Biomedical domain
Type de document :
Communication dans un congrès
Domaine :
> Informatique [cs]
> Informatique [cs] / Intelligence artificielle [cs.AI]
Liste complète des métadonnées Voir
--------------------------------------------------------------------------------
https://hal.archives-ouvertes.fr/hal-03853319
Contributeur : Martinez-Gil Jorge Connectez-vous pour contacter le contributeur
Soumis le : mardi 15 novembre 2022 - 12:31:49
Dernière modification le : mardi 22 novembre 2022 - 10:08:11
IDENTIFIANTS
* HAL Id : hal-03853319, version 1
* DOI : 10.1145/3487664.3487781
COLLECTIONS
UNIV-TLSE2 | CNRS | UT1-CAPITOLE | IRIT | IRIT-PYRAMIDE | IRIT-GD | UNIV-UT3 |
UT3-TOULOUSEINP
CITATION
Jorge Martinez-Gil, Shaoyi Yin, Josef Küng, Franck Morvan. Matching Large
Biomedical Ontologies Using Symbolic Regression. 23rd International Conference
on Information Integration and Web Intelligence (iiWAS 2021), Nov 2021, Linz,
Austria. pp.162-167, ⟨10.1145/3487664.3487781⟩. ⟨hal-03853319⟩
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