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YAM-BIO – Results for OAEI 2017

Amina Annane 1 Zohra Bellahsene 1 Faiçal Azouaou 2 Clement Jonquet 3, 4
1 FADO - Fuzziness, Alignments, Data & Ontologies
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
3 SMILE - Système Multi-agent, Interaction, Langage, Evolution
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : The YAM-BIO ontology alignment system is an extension of YAM++ but dedicated to aligning biomedical ontologies. YAM++ has successfully participated in several editions of the Ontology Alignment Evaluation Initiative (OAEI) between 2011 and 2013, but this is the first participation of YAM-BIO. The biomedical extension includes a new component that uses existing mappings between multiple biomedi-cal ontologies as background knowledge. In this short system paper, we present YAM-BIO's workflow and the results obtained in the Anatomy and Large Biomedical Ontologies tracks of the OAEI 2017 campaign. 1 Presentation of the YAM-BIO system 1.1 State, purpose, general statement YAM-BIO may be seen as an extension of YAM++ [5] that uses existing map-pings between multiple biomedical ontologies as background knowledge to enhance the matching results. The latest version of YAM++, which we reused in YAM-BIO, obtained excellent results in multiple Ontology Alignment Evaluation Initiative (OAEI) campaigns, especially in 2013 [11]. YAM++ did not participate more since then. Four years on from the last participation, our objective this year was to establish a comparison between the potential performance of a bio-customized YAM++, and state-of-the-art systems in matching biomedical ontologies. Over last OAEI campaigns, state-of-the-art systems such as AML [7] and LogMapBio [9] used specialized background knowledge to improve their results. More generally, the use of background knowledge –or indirect matching techniques– as recently allowed to obtain better results. YAM-BIO is an equivalent evolution of YAM++ in which we added a component that uses existing mappings as background knowledge. With YAM-BIO, we participated this year to the Anatomy and Large Biomedical Ontologies (Largebio) tracks.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01679503
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Amina Annane, Zohra Bellahsene, Faiçal Azouaou, Clement Jonquet. YAM-BIO – Results for OAEI 2017. 2017, pp.1-6. ⟨lirmm-01679503⟩

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