A fault model for ontology mapping, alignment, and linking systems.
There has been much work devoted to the mapping, alignment, and linking of ontologies (MALO), but little has been published about how to evaluate systems that do this. A fault model for conducting fine-grained evaluations of MALO systems is proposed, and its application to the system described in Johnson et al. [15] is illustrated. Two judges categorized errors according to the model, and inter-judge agreement was calculated by error category. Overall inter-judge agreement was 98% after dispute resolution, suggesting that the model is consistently applicable. The results of applying the model to the system described in [15] reveal the reason for a puzzling set of results in that paper, and also suggest a number of avenues and techniques for improving the state of the art in MALO, including the development of biomedical domain specific language processing tools, filtering of high frequency matching results, and word sense disambiguation.
Johnson
Helen L
HL
Center for Computational Pharmacology, School of Medicine, University of Colorado, Aurora, CO 80045, USA. Helen.Johnson@uchsc.edu
Cohen
K Bretonnel
KB
Hunter
Lawrence
L
D019295:Computational Biology; D008954:Models, Biological; D015233:Models, Statistical; D009323:Natural Language Processing; D012984:Software