Can Yang

Orcid: 0000-0001-5361-6034

Affiliations:
  • KTH - Royal Institution of Technology, Division of Geoinformatics Sweden


According to our database1, Can Yang authored at least 13 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2024
Spatio-temporal intention learning for recommendation of next point-of-interest.
Geo spatial Inf. Sci., March, 2024

Detecting road network errors from trajectory data with partial map matching and bidirectional recurrent neural network model.
Int. J. Geogr. Inf. Sci., March, 2024

Generating lane-level road networks from high-precision trajectory data with lane-changing behavior analysis.
Int. J. Geogr. Inf. Sci., February, 2024

2023
Multi-agent reinforcement learning to unify order-matching and vehicle-repositioning in ride-hailing services.
Int. J. Geogr. Inf. Sci., 2023

2022
Spatial-Temporal Diffusion Convolutional Network: A Novel Framework for Taxi Demand Forecasting.
ISPRS Int. J. Geo Inf., 2022

Multi-view Self-attention Network for Next POI Recommendation.
Proceedings of the IEEE Smartworld, 2022

2021
The Integration of Linguistic and Geospatial Features Using Global Context Embedding for Automated Text Geocoding.
ISPRS Int. J. Geo Inf., 2021

2020
Efficient Map Matching and Discovery of Frequent and Dominant Movement Patterns in GPS Trajectory Data.
PhD thesis, 2020

Detecting regional dominant movement patterns in trajectory data with a convolutional neural network.
Int. J. Geogr. Inf. Sci., 2020

LPM: a latent probit model to characterize the relationship among complex traits using summary statistics from multiple GWASs and functional annotations.
Bioinform., 2020

2018
Mining and visual exploration of closed contiguous sequential patterns in trajectories.
Int. J. Geogr. Inf. Sci., 2018

Fast map matching, an algorithm integrating hidden Markov model with precomputation.
Int. J. Geogr. Inf. Sci., 2018

2015
Scalable Detection of Traffic Congestion from Massive Floating Car Data Streams.
Proceedings of the 1st International ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics, 2015


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