Author

Wolfram Höpken

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Preprint Aug 2026

POI Recommendation with LLM-Augmented Multi-Graph Learning and Contrastive Alignment

The proposed LLM-augmented Multi-Graph Contrastive Learning (LLM-MGCL) is a multi-graph neural network that uses semantic and spatial information about items to extend the LightGCN backbone with two auxiliary item-item graphs that outperforms classical collaborative filtering, matrix factorization, and interaction-only graph neural network baselines.

Burak Tamer, Wolfram Höpken, Zehui Wang · 0 citations