4 citations · 5 across the 3 of their papers we have counts for
3 papers
A global analysis of metrics used for measuring performance in natural language processing
Kathrin Blagec, Georg Dorffner, Milad Moradi +2
Measuring the performance of natural language processing models is challenging. Traditionally used metrics, such as BLEU and ROUGE, originally devised for machine translation and s…
A curated, ontology-based, large-scale knowledge graph of artificial intelligence tasks and benchmarks
Kathrin Blagec, Adriano Barbosa-Silva, Simon Ott +1
Research in artificial intelligence (AI) is addressing a growing number of tasks through a rapidly growing number of models and methodologies. This makes it difficult to keep track…
Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphs
Simon Ott, Laura Graf, Asan Agibetov +2
Neural embedding-based machine learning models have shown promise for predicting novel links in biomedical knowledge graphs. Unfortunately, their practical utility is diminished by…