Research map / Label-efficient and robust learning / Recognition and long-tail
POI2Vec: Geographical Latent Representation for Predicting Future Visitors
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| replace Huffman tree with geographic region binary tree (multi-region POI assignment) in hierarchical softmax (ablation) | word2vec HS · Foursquare next POI | Pre@5: +16% | Helped |
| POI2Vec joint representation with Sum aggregation vs FPMC | future visitor prediction · Foursquare | Pre@5: +29% | Helped |
| add sequential transition from recent position to user preference (SUM vs U) (ablation) | POI2Vec · Foursquare, Gowalla | Pre@N | Helped |
| include users without recent positions (SUM vs URP) (ablation) | POI2Vec · Foursquare, Gowalla | Pre@N | Helped |
| Sum aggregation instead of Max (ablation) | POI2Vec · Foursquare, Gowalla | Pre@N | Helped |
| increase region size threshold theta (ablation) | POI2Vec · Foursquare, Gowalla | Pre@10 | Mixed |
| increase embedding dimension D (ablation) | POI2Vec · Foursquare, Gowalla | Pre@10 | Helped |
Closest papers by meaning
- GeoMamba: Towards Multi-granular POI Recommendation with Geographical State Space Model (AAAI 2025 · similarity 0.92)
- Integrating Personalized Spatio-Temporal Clustering for Next POI Recommendation (AAAI 2025 · similarity 0.90)
- Enhancing Long-and Short-Term Representations for Next POI Recommendations via Frequency and Hierarchical Contrastive Learning (AAAI 2025 · similarity 0.88)
- Learning Time Slot Preferences via Mobility Tree for Next POI Recommendation (AAAI 2024 · similarity 0.88)
- SPOT-Trip: Dual-Preference Driven Out-of-Town Trip Recommendation (NeurIPS 2025 · similarity 0.87)
- TAU: Trajectory Data Augmentation with Uncertainty for Next POI Recommendation (AAAI 2024 · similarity 0.87)
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