April 20, 2022, 1:12 a.m. | Charles Tapley Hoyt, Max Berrendorf, Mikhail Galkin, Volker Tresp, Benjamin M. Gyori

cs.LG updates on arXiv.org arxiv.org

The link prediction task on knowledge graphs without explicit negative
triples in the training data motivates the usage of rank-based metrics. Here,
we review existing rank-based metrics and propose desiderata for improved
metrics to address lack of interpretability and comparability of existing
metrics to datasets of different sizes and properties. We introduce a simple
theoretical framework for rank-based metrics upon which we investigate two
avenues for improvements to existing metrics via alternative aggregation
functions and concepts from probability theory. We …

arxiv evaluation framework graphs knowledge knowledge graphs link prediction metrics prediction

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