| 0 |
Crime Rate Inference with Big Data |
Crime Rate Inference |
📝KDD |
|
2016 |
| 1 |
Modeling Temporal-Spatial Correlations for Crime Prediction |
Crime Prediction |
📝CIKM |
|
2017 |
| 3 |
Non-Stationary Model for Crime Rate Inference Using Modern Urban Data |
Crime Rate Inference |
📝IEEE TBD |
|
2017 |
| 4 |
DeepCrime: Attentive Hierarchical Recurrent Networks for Crime Prediction |
Crime Prediction |
📝CIKM |
|
2018 |
| 5 |
An Integrated Model for Crime Prediction Using Temporal and Spatial Factors |
Crime Prediction |
📝ICDM |
|
2018 |
| 6 |
Crime in Urban Areas: A Data Mining Perspective |
Crime Prediction |
📝ICDM |
|
2018 |
| 7 |
Neural Network based Continuous Conditional Random Field for Fine-grained Crime Prediction |
Crime Prediction |
📝IJCAI |
|
2019 |
| 8 |
Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information |
Crime Prediction |
📝KDD |
|
2019 |
| 9 |
MiST: A Multiview and Multimodal Spatial-Temporal Learning Framework for Citywide Abnormal Event Forecasting |
Crime Prediction |
📝KDD |
|
2019 |
| 10 |
Modelling Regional Crime Risk using Directed Graph of Check-ins |
Crime; Human Mobility |
📝CIKM |
|
2020 |
| 11 |
Hierarchically Structured Transformer Networks for Fine-Grained Spatial Event Forecasting |
Crime Prediction |
📝WWW |
|
2020 |
| 12 |
Spatio-Temporal-Categorical Graph Neural Networks for Fine-Grained Multi-Incident Co-Prediction |
Crime Prediction |
📝CIKM |
|
2021 |
| 13 |
Crime Prediction with Graph Neural Networks and Multivariate Normal Distributions |
Crime Prediction |
📝ARXIV |
|
2021 |
| 14 |
Multi-type Urban Crime Prediction |
Crime Prediction |
📝AAAI |
|
2022 |
| 15 |
Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction |
Crime Prediction |
📝ICDM |
Code |
2022 |
| 16 |
Spatial-Temporal Meta-path Guided Explainable Crime Prediction |
Crime Prediction |
📝ARXIV |
|
2022 |