Explaining GNN-based Recommendations in Logic

Summary: Introduce Makex, a logic-based explanation framework that discovers Rules for ExPlanations (REPs)—a graph pattern Q plus precondition predicates X→M(x,y)—to expose topology and feature dependencies driving GNN recommender outputs. Defines REPs via 1-WL, gives algorithms for global REP discovery and top-k local explanations, and reports superior fidelity, sparsity, and efficiency versus prior methods. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 14232
Venue: VLDB
Year: 2025
Pagerank: 4.3399748e-05
Overall Rank: 9,406 | 34.63%
DOI: 10.14778/3712221.3712237

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,233	Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling	2026	VLDB	4.1905499e-05

Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,188	word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings of Structured Data	2020	PODS	0.00013431099
1,869	Interpretable Data-Based Explanations for Fairness Debugging	2022	SIGMOD	0.00010263235
2,517	Dependencies for Graphs	2017	PODS	8.6058545e-05
3,478	Functional Dependencies for Graphs	2016	SIGMOD	7.0554625e-05
5,120	Association Rules with Graph Patterns	2015	VLDB	5.6754325e-05
6,156	On Data-Aware Global Explainability of Graph Neural Networks	2023	VLDB	5.1779507e-05
8,135	Towards Event Prediction in Temporal Graphs	2022	VLDB	4.5740737e-05
8,145	Capturing Associations in Graphs	2020	VLDB	4.5724134e-05
9,489	Making It Tractable to Catch Duplicates and Conflicts in Graphs	2023	SIGMOD	4.3300131e-05
11,211	Enriching Recommendation Models with Logic Conditions	2023	SIGMOD	4.1905499e-05

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