Reevaluation of Inductive Link Prediction
Reevaluation of Inductive Link Prediction
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Ithaca: Cornell University Library, arXiv.org
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English
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Publisher
Ithaca: Cornell University Library, arXiv.org
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Contents
Within this paper, we show that the evaluation protocol currently used for inductive link prediction is heavily flawed as it relies on ranking the true entity in a small set of randomly sampled negative entities. Due to the limited size of the set of negatives, a simple rule-based baseline can achieve state-of-the-art results, which simply ranks en...
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Full title
Reevaluation of Inductive Link Prediction
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TN_cdi_proquest_journals_3111723095
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3111723095
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E-ISSN
2331-8422
DOI
10.48550/arxiv.2409.20130
