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Efficient Embeddings of Logical Variables for Query Answering over Incomplete Knowledge Graphs

AAAI 2023 · Graph learning › Knowledge and temporal graphs · approach: Logical query answering and rule reasoning · 10 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use Var2Vec rather than the strongest reported negation-free baselinecomplex query answering · NELL995, negation-free queriesMRR (%): 28.8 -> 30.1Helped
use Var2Vec rather than the strongest reported negation-free baselinecomplex query answering · FB15k-237, negation-free queriesMRR (%): 23.2 -> 23.4Helped
use Var2Vec rather than the strongest reported negation-free baselinecomplex query answering · FB15k, negation-free queriesMRR (%): 49.7 -> 51.0Helped
use Var2Vec rather than the strongest reported baseline supporting negationcomplex query answering · NELL995, queries with negationMRR (%): 7.3 -> 7.5Helped
use Var2Vec rather than the strongest reported baseline supporting negationcomplex query answering · FB15k-237, queries with negationMRR (%): 6.7 -> 6.4Hurt
use Var2Vec rather than the strongest reported baseline supporting negationcomplex query answering · FB15k, queries with negationMRR (%): 14.8 -> 18.9Helped
replace ComplEx with DistMult (ablation)Var2Vec · NELL995, negation-free queriesMRR (%): 30.1 -> 28.1Hurt
replace ComplEx with DistMult (ablation)Var2Vec · FB15k-237, negation-free queriesMRR (%): 23.2 -> 21.6Hurt
replace ComplEx with DistMult (ablation)Var2Vec · FB15k, negation-free queriesMRR (%): 51.0 -> 41.8Hurt
replace product t-norm and t-conorm with Gödel min-max operators (ablation)Var2Vec · NELL995, negation-free queriesMRR (%): 30.1 -> 25.9Hurt
replace product t-norm and t-conorm with Gödel min-max operators (ablation)Var2Vec · FB15k-237, negation-free queriesMRR (%): 23.2 -> 19.4Hurt
replace product t-norm and t-conorm with Gödel min-max operators (ablation)Var2Vec · FB15k, negation-free queriesMRR (%): 51.0 -> 45Hurt

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