YAM-BIO: results for OAEI 2017
نویسندگان
چکیده
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 biomedical 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 mappings 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. 1.2 YAM-BIO’s general alignment worklfow As illustrated in Fig. 1, YAM-BIO’s workflow contains three main steps: First, to compute direct matching between source and target ontologies using YAM++.
منابع مشابه
YAM++ results for OAEI 2011
The YAM++ system is a self configuration, flexible and extensible ontology matching system. The key idea behind YAM++ system is based on machine learning and similarity flooding approaches. In this paper, we briefly present the YAM++ and its results on Benchmark and Conference tracks on OAEI
متن کاملCroLOM results for OAEI 2017: summary of cross-lingual ontology matching systems results at OAEI
This paper presents the results obtained in the OAEI 2017 campaign by our ontology matching system CroLOM. CroLOM is an automatic system especially designed for aligning multilingual ontologies. This is our second participation with CroLOM in the OAEI and the results have so far been positive.
متن کاملYAM++ results for OAEI 2012
The YAM++ system is a self configuration, flexible and extensible ontology matching system. YAM++ takes advantages of many techniques coming from different fields such as machine learning, information retrieval, graph matching, etc. in order to enhance the matching quality. In this paper, we briefly present the YAM++ approach and its results on OAEI 2012 campaign. 1 Presentation of the system Y...
متن کاملONTMAT: results for OAEI 2017
This paper describes ONTMAT an ontology matching system, and presents the results obtained for the Ontology Alignment Evaluation Initiative (OAEI) 2017. ONTMAT is an ontology matching process, which compares the instances of ontologies to align in order to deduce the relations between their concepts. Then, based on hierarchical and binary relations between the concepts inside the ontologies it ...
متن کاملPOMap results for OAEI 2017
Ontology matching is an effective strategy to find the correspondences among different ontologies in a scalable and a heterogeneous semantic web. In order to find these correspondences, a matching system should be built aiming to ensure the interoperability between ontologies. POMap (Pairwise Ontology Mapping) is an automated ontology matching system dealing with the three main types of heterog...
متن کامل