MDE: Multiple Distance Embeddings for Link Prediction in Knowledge Graphs
Table 6: Results of MDE after 100 iterations when removing one of the terms. Best results are in bold.
['Removed Term', 'MR', '[BOLD] WN18RR MRR', 'Hit@10', 'MR', '[BOLD] WIN18 MRR', 'Hit@10']
The evaluations on WN18RR and WN18 show that the removal of S4 has the most negative effect on the performance of MDE. The removal of S1 that was one of the good performing terms in the last experiment has the least effect. Nevertheless, S1 improves the MRR in the MDE. Also, when we remove S2, the MRR and Hit@10 are negatively influenced, indicating that it exists cases that S2 performs better than the other terms, although, in the individual tests, it performed the worst between all the terms.