mlsanityData to 14 Oct 2026

TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multifaceted Graph Modeling

arXiv 2401.03138 ↗First posted 6 Jan 2024cs.LG cs.AIcited by 3

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Abstract (arXiv)

To address the limitations of traffic prediction from location-bound detectors, we present Geographical Cellular Traffic (GCT) flow, a novel data source that leverages the extensive coverage of cellular traffic to capture mobility patterns. Our extensive analysis validates its potential for transportation. Focusing on vehicle-related GCT flow prediction, we propose a graph neural network that integrates multivariate, temporal, and spatial facets for improved accuracy. Experiments reveal our model's superiority over baselines, especially in long-term predictions. We also highlight the potential for GCT flow integration into transportation systems.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 11 of its 26 references that are in the map. First posted on arXiv 6 Jan 2024.

Builds on

11 of 26 references.

References · 11

  1. 2017Graph Attention Networkscited by 8,923
  2. 2017Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecastingcited by 1,136
  3. 2015Multi-Scale Context Aggregation by Dilated Convolutionscited by 1,133
  4. 2019Graph WaveNet for Deep Spatial-Temporal Graph Modelingcited by 829
  5. 2020Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networkscited by 566
  6. 2019GMAN: A Graph Multi-Attention Network for Traffic Predictioncited by 434
  7. 2021Graph Neural Network-Based Anomaly Detection in Multivariate Time Seriescited by 301
  8. 2020Multivariate Time-series Anomaly Detection via Graph Attention Networkcited by 167
  9. 2022Long-term Spatio-temporal Forecasting via Dynamic Multiple-Graph Attentioncited by 15
  10. 2021Multivariate and Propagation Graph Attention Network for Spatial-Temporal Prediction with Outdoor Cellular Trafficcited by 7
  11. 2015Computational Network Design from Functional Specificationscited by 4

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Cited by year

Citing papers per year: 2024: 2; 2025: 1.

3 papers.

  1. 2025CrossLinear: Plug-and-Play Cross-Correlation Embedding for Time Series Forecasting with Exogenous Variablescited by 22
  2. 2024Tel2Veh: Fusion of Telecom Data and Vehicle Flow to Predict Camera-Free Traffic via a Spatio-Temporal Frameworkcited by 0
  3. 2024Enhancing Sustainable Urban Mobility Prediction with Telecom Data: A Spatio-Temporal Framework Approachcited by 0