Completing the princeton annotated gloss corpus project
Alexandre Rademaker, Bruno Cuconato, et al.
GWC 2019
Ontologies are computational artifacts that model consensual aspects of reality. In distributed contexts, applications often need to utilize information from several distinct ontologies. In order to integrate multiple ontologies, entities modeled in each ontology must be matched through an ontology alignment. However, imperfect alignments may introduce inconsistencies. One kind of inconsistency, which is often introduced, is the violation of the conservativity principle, that states that the alignment should not introduce new subsumption relations between entities from the same source ontology. We propose a two-step quadratic-time algorithm for automatically correcting such violations, and evaluate it against datasets from the Ontology Alignment Evaluation Initiative 2019, comparing the results to a state-of-the-art approach. The proposed algorithm was significantly faster and less aggressive; that is, it performed fewer modifications over the original alignment when compared to the state-of-the-art algorithm.
Alexandre Rademaker, Bruno Cuconato, et al.
GWC 2019
John P. McCrae, Michael Wayne Goodman, et al.
GWC 2021
Valeria de Paiva, Livy Real, et al.
GWC 2016
Joel Luís Carbonera, Mara Abel
ICTAI 2017