Representation learning for general graph data and five types of spatio-temporal data:
| Model | Paper | Publication | Code | Remarks |
|---|---|---|---|---|
| General Graph/Network | OpenNE | GraphEmbedding | graph_nets | |
| DeepWalk | DeepWalk: Online Learning of Social Representations | KDD 2014 | Code | LibCity-Road-Representation |
| Node2Vec | node2vec: Scalable Feature Learning for Networks | KDD 2016 | Code | LibCity-Road-Representation |
| LINE | Line: Large-scale information network embedding | WWW 2015 | Code | LibCity-Road-Representation |
| ChebConv | Convolutional neural networks on graphs with fast localized spectral filtering | NIPS 2016 | Code | LibCity-Road-Representation |
| GCN | Semi-Supervised Classification with Graph Convolutional Networks | ICLR 2017 | Code | |
| GAT | Graph Attention Networks | ICLR 2017 | Code | LibCity-Road-Representation |
| GraphSAGE | Inductive Representation Learning on Large Graphs | NIPS 2017 | Code | |
| metapath2vec | metapath2vec: Scalable representation learning for heterogeneous networks | KDD 2017 | Code | |
| Geom-GCN | Geom-GCN: Geometric Graph Convolutional Networks. | ICLR 2020 | Code | LibCity-Road-Representation |
| Model | Paper | Publication | Code | Remarks |
|---|---|---|---|---|
| ship-gram | Efficient estimation of word representations in vector space | ICLR 2013 | Code | |
| GE | Learning Graph-based POI Embedding for Location-based Recommendation | CIKM 2016 | ||
| POI2Vec | POI2Vec: Geographical Latent Representation for Predicting Future Visitors | AAAI 2017 | ||
| Geo-teaser | Geo-teaser: Geo-temporal sequential embedding rank for point-of-interest recommendation | WWW 2017 | ||
| CAPE | Content-Aware Hierarchical Point-of-Interest Embedding Model for Successive POI Recommendation | IJCAI 2018 | ||
| DKFM | Location Embeddings for Next Trip Recommendation | WWW 2019 | ||
| HIER | Learning Fine Grained Place Embeddings with Spatial Hierarchy from Human Mobility Trajectories. | arxiv 2020 | ||
| TALE | Pre-training Time-Aware Location Embeddings from Spatial-Temporal Trajectories | TKDE 2021 | ||
| CTLE | Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction | AAAI 2021 | Code | |
| PPR | Spatio-Temporal Representation Learning with Social Tie for Personalized POI Recommendation | Data Science and Engineering 2022 | ||
| CatEM | Pre-Trained Semantic Embeddings for POI Categories Based on Multiple Contexts | TKDE 2022 | ||
| HE-LMF | POI Recommendation System using Hypergraph Embedding and Logical Matrix Factorization | Journal of Artificial Intelligence and Capsule Networks 2022 |
| Model | Paper | Publication | Code | Remarks |
|---|---|---|---|---|
| IRN2Vec | Learning Embeddings of Intersections on Road Networks | SIGSPATIAL 2019 | Code | Intersections |
| RFN | Graph Convolutional Networks for Road Networks | SIGSPATIAL 2019 | Intersections | |
| SRN2Vec | On Representation Learning for Road Networks | TIST 2020 | Intersections/Road Segment | |
| HRNR | Learning Effective Road Network Representation with Hierarchical Graph Neural Networks | KDD 2020 | Code | Road Segment，supervised |
| Toast | Robust Road Network Representation Learning: When Traffic Patterns Meet Traveling Semantics | CIKM 2021 | Road Segment，self-supervised | |
| A Multiview Representation Learning Framework for Large-Scale Urban Road Networks | MDPI 2022 | Road Segment | ||
| JCLRNT | Jointly Contrastive Representation Learning on Road Network and Trajectory | CIKM 2022 | Code | Road Segment，self-supervised |
| SARN | Spatial Structure-Aware Road Network Embedding via Graph Contrastive Learning | EBDT 2023（CCF-B） | Road Segment，self-supervised |
| Model | Paper | Publication | Code | Remarks |
|---|---|---|---|---|
| HDGE | Region representation learning via mobility flow | CIKM 2017 | word2vec | |
| ZE-Mob | Representing urban functions through zone embedding with human mobility patterns | IJCAI 2018 | word2vec | |
| Learning urban community structures: A collective embedding perspective with periodic spatial-temporal mobility graphs | TIST 2018 | Auto-Encoder | ||
| CGAL | Unifying inter-region autocorrelation and intra-region structures for spatial embedding via collective adversarial learning | KDD 2019 | Auto-Encoder | |
| MP-VN | Efficient region embedding with multi-view spatial networks: A perspective of locality-constrained spatial autocorrelations | AAAI 2019 | Auto-Encoder | |
| GEML | GEML: Learning Geo-Contextual Embeddings for Commuting Flow Prediction | AAAI 2020 | Code | |
| MVURE | Multi-View Joint Graph Representation Learning for Urban Region Embedding | IJCAI 2020 | Code | multi-graph |
| HUGAT | Effective Urban Region Representation Learning Using Heterogeneous Urban Graph Attention Network | arxiv 2022 | heterogeneous graph | |
| Region2Vec | Region2Vec: Urban Region Profiling via A Multi-Graph Representation Learning Framework | CIKM 2022 | multi-graph | |
| MGFN | Multi-Graph Fusion Networks for Urban Region Embedding | IJCAI 2022 | Code | multi-graph |
| RELM | Learning Time and Type Aware Representations for Urban Zones | SSRN 2022 | time-aware | |
| HGI | Learning urban region representations with POIs and hierarchical graph infomax | ISPRS Journal of Photogrammetry and Remote Sensing 2023 | Code | POI-Region |
| Unsupervised Representation Learning of Spatial Data via Multimodal Embedding | CIKM 2019 | Multimodal | ||
| Urban2Vec | Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding | AAAI 2020 | Multimodal | |
| Learning Neighborhood Representation from Multi-Modal Multi-Graph: Image, Text, Mobility Graph and Beyond | arxiv 2021 | Multimodal |
| Model | Paper | Publication | Code | Remarks |
|---|---|---|---|---|
| trajectory2vec | trajectory2vec: Trajectory clustering via deep representation learning | IJCNN 2017 | Code | encoder-decoder |
| t2vec | Deep Representation Learning for Trajectory Similarity Computation | ICDE 2018 | Code | encoder-decoder |
| Trembr | Trembr: Exploring Road Networks for Trajectory Representation Learning | TIST 2020 | self-supervised | |
| Path-InfoMax | Unsupervised Path Representation Learning with Curriculum Negative Sampling | IJCAI 2021 | Code | self-supervised |
| Toast | Robust Road Network Representation Learning: When Traffic Patterns Meet Traveling Semantics | CIKM 2021 | self-supervised | |
| JCLRNT | Jointly Contrastive Representation Learning on Road Network and Trajectory | CIKM 2022 | Code | self-supervised |
| CSTRM | CSTRM: Contrastive Self-Supervised Trajectory Representation Model for trajectory similarity computation | Computer Communications 2022 | self-supervised | |
| WSCCL | Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning | ICDE 2022 | Code | weakly-supervised |
| START | Self-supervised Trajectory Representation Learning with Temporal Regularities and Travel Semantics | ICDE 2023 | Code | self-supervised |
| CSTTE | Contrastive Pre-training of Spatial-Temporal Trajectory Embeddings | arxiv 2022 | self-supervised |
| Model | Paper | Publication | Code | Remarks |
|---|---|---|---|---|
| TRED | Semi-supervised Trajectory Understanding with POI Attention for End-to-End Trip Recommendation | TSAS 2020 | semi-supervised | |
| GTS | A graph-based approach for trajectory similarity computation in spatial networks | KDD 2021 | ||
| SelfTrip | Self-supervised Representation Learning for Trip Recommendation | KBS 2022 | self-supervised | |
| CTLTR | Contrastive Trajectory Learning for Tour Recommendation | TIST 2022 | self-supervised | |
| Contrastive Pre-training with Adversarial Perturbations for Check-in Sequence Representation Learning | AAAI 2023 | self-supervised |