mlsanityData to 7 Oct 2026

GETNext: Trajectory Flow Map Enhanced Transformer for Next POI Recommendation

arXiv 2303.04741 ↗First posted 3 Mar 2023cs.IR cs.LGcited by 57

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Abstract (arXiv)

Next POI recommendation intends to forecast users' immediate future movements given their current status and historical information, yielding great values for both users and service providers. However, this problem is perceptibly complex because various data trends need to be considered together. This includes the spatial locations, temporal contexts, user's preferences, etc. Most existing studies view the next POI recommendation as a sequence prediction problem while omitting the collaborative signals from other users. Instead, we propose a user-agnostic global trajectory flow map and a novel Graph Enhanced Transformer model (GETNext) to better exploit the extensive collaborative signals for a more accurate next POI prediction, and alleviate the cold start problem in the meantime. GETNext incorporates the global transition patterns, user's general preference, spatio-temporal context, and time-aware category embeddings together into a transformer model to make the prediction of user's future moves. With this design, our model outperforms the state-of-the-art methods with a large margin and also sheds light on the cold start challenges within the spatio-temporal involved recommendation problems.

Key facts. Cited by 57 papers in the map (data through 7 Oct 2026). Builds on 9 of its 34 references that are in the map. First posted on arXiv 3 Mar 2023.

Builds on

9 of 34 references.

References · 9

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  4. 2019Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecastingcited by 748
  5. 2015LINE: Large-scale Information Network Embeddingcited by 582
  6. 2021Video Transformer Networkcited by 271
  7. 2019Time2Vec: Learning a Vector Representation of Timecited by 208
  8. 2021STAN: Spatio-Temporal Attention Network for Next Location Recommendationcited by 102
  9. 2021Discovering Collaborative Signals for Next POI Recommendation with Iterative Seq2Graph Augmentationcited by 20

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 20; 2025: 18; 2026: 12.

57 papers.

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  1. 2024Large Language Models for Next Point-of-Interest Recommendationcited by 40
  2. 2023A Diffusion model for POI recommendationcited by 24
  3. 2024Mobility-LLM: Learning Visiting Intentions and Travel Preferences from Human Mobility Data with Large Language Modelscited by 21
  4. 2024Where to Move Next: Zero-shot Generalization of LLMs for Next POI Recommendationcited by 17
  5. 2024A Survey of Generative Techniques for Spatial-Temporal Data Miningcited by 14
  6. 2023Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptationcited by 13
  7. 2024TrajGPT: Controlled Synthetic Trajectory Generation Using a Multitask Transformer-Based Spatiotemporal Modelcited by 13
  8. 2024A Survey on Point-of-Interest Recommendation: Models, Architectures, and Securitycited by 12
  9. 2023Revisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest Recommendationcited by 11
  10. 2023A Hierarchical Spatial Transformer for Massive Point Samples in Continuous Spacecited by 10
  11. 2024A Universal Model for Human Mobility Predictioncited by 10
  12. 2024LIMP: Large Language Model Enhanced Intent-aware Mobility Predictioncited by 8
38 more
  1. 2024Taming the Long Tail in Human Mobility Predictioncited by 8
  2. 2024RED: Effective Trajectory Representation Learning with Comprehensive Informationcited by 8
  3. 2025CoMaPOI: A Collaborative Multi-Agent Framework for Next POI Prediction Bridging the Gap Between Trajectory and Languagecited by 8
  4. 2024Learning Time Slot Preferences via Mobility Tree for Next POI Recommendationcited by 7
  5. 2024Geo-Llama: Leveraging LLMs for Human Mobility Trajectory Generation with Spatiotemporal Constraintscited by 7
  6. 2023Spatial-Temporal Interplay in Human Mobility: A Hierarchical Reinforcement Learning Approach with Hypergraph Representationcited by 6
  7. 2024MAS4POI: a Multi-Agents Collaboration System for Next POI Recommendationcited by 6
  8. 2024NextLocLLM: Location Semantics Modeling and Coordinate-Based Next Location Prediction with LLMscited by 5
  9. 2024REPLAY: Modeling Time-Varying Temporal Regularities of Human Mobility for Location Prediction over Sparse Trajectoriescited by 3
  10. 2025Massive-STEPS: Massive Semantic Trajectories for Understanding POI Check-ins -- Dataset and Benchmarkscited by 3
  11. 2025Adaptive Location Hierarchy Learning for Long-Tailed Mobility Predictioncited by 3
  12. 2025Beyond Regularity: Modeling Chaotic Mobility Patterns for Next Location Predictioncited by 3
  13. 2026Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movementcited by 3
  14. 2026ELLMob: Event-Driven Human Mobility Generation with Self-Aligned LLM Frameworkcited by 3
  15. 2023Where have you been? A Study of Privacy Risk for Point-of-Interest Recommendationcited by 2
  16. 2024Spatial-Temporal Cross-View Contrastive Pre-training for Check-in Sequence Representation Learningcited by 2
  17. 2024Back to Bayesics: Uncovering Human Mobility Distributions and Anomalies with an Integrated Statistical and Neural Frameworkcited by 2
  18. 2025Geography-Aware Large Language Models for Next POI Recommendationcited by 2
  19. 2025Mixture-of-Experts for Personalized and Semantic-Aware Next Location Predictioncited by 2
  20. 2026CaST-POI: Candidate-Conditioned Spatiotemporal Modeling for Next POI Recommendationcited by 2
  21. 2023Optimizing Group Utility in Itinerary Planning: A Strategic and Crowd-Aware Approachcited by 1
  22. 2024Bi-Level Graph Structure Learning for Next POI Recommendationcited by 1
  23. 2024Forecasting Unseen Points of Interest Visits Using Context and Proximity Priorscited by 1
  24. 2025MoveGPT: Scaling Mobility Foundation Models with Spatially-Aware Mixture of Expertscited by 1
  25. 2025AdaptGOT: A Pre-trained Model for Adaptive Contextual POI Representation Learningcited by 1
  26. 2025MoveFM-R: Advancing Mobility Foundation Models via Language-driven Semantic Reasoningcited by 1
  27. 2025Next Point-of-interest (POI) Recommendation Model Based on Multi-modal Spatio-temporal Context Feature Embeddingcited by 1
  28. 2024TrajGEOS: Trajectory Graph Enhanced Orientation-based Sequential Network for Mobility Predictioncited by 0
  29. 2025Where to Go Next Day: Multi-scale Spatial-Temporal Decoupled Model for Mid-term Human Mobility Predictioncited by 0
  30. 2025Causality-Aware Next Location Prediction Framework based on Human Mobility Stratificationcited by 0
  31. 2025Efficient Temporal Tokenization for Mobility Prediction with Large Language Modelscited by 0
  32. 2025Enhancing POI Recommendation through Global Graph Disentanglement with POI Weighted Modulecited by 0
  33. 2025Analyzing and Mitigating Repetitions in Trip Recommendationcited by 0
  34. 2025Disentangling Multiplex Spatial-Temporal Transition Graph Representation Learning for Socially Enhanced POI Recommendationcited by 0
  35. 2025STRelay: A Universal Spatio-Temporal Relaying Framework for Location Prediction over Human Trajectory Datacited by 0
  36. 2025GPS-MTM: Capturing Pattern of Normalcy in GPS-Trajectories with self-supervised learningcited by 0
  37. 2026Mag-Mamba: Modeling Coupled spatiotemporal Asymmetry for POI Recommendationcited by 0
  38. 2026Exploration Space Theory: Formal Foundations for Prerequisite-Aware Location-Based Recommendationcited by 0

50 most cited of 57 All 57 (JSON)