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- research-articleAugust 2024
Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction
KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2024, Pages 5206–5217https://doi.org/10.1145/3637528.3671507Rapid urbanization has significantly escalated traffic congestion, underscoring the need for advanced congestion prediction services to bolster intelligent transportation systems. As one of the world's largest ride-hailing platforms, DiDi places great ...
BigST: Linear Complexity Spatio-Temporal Graph Neural Network for Traffic Forecasting on Large-Scale Road Networks
Proceedings of the VLDB Endowment (PVLDB), Volume 17, Issue 5Pages 1081–1090https://doi.org/10.14778/3641204.3641217Spatio-Temporal Graph Neural Network (STGNN) has been used as a common workhorse for traffic forecasting. However, most of them require prohibitive quadratic computational complexity to capture long-range spatio-temporal dependencies, thus hindering ...
- research-articleDecember 2023
Improving First-stage Retrieval of Point-of-interest Search by Pre-training Models
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 3Article No.: 74, Pages 1–27https://doi.org/10.1145/3631937Point-of-interest (POI) search is important for location-based services, such as navigation and online ride-hailing service. The goal of POI search is to find the most relevant destinations from a large-scale POI database given a text query. To improve ...
- research-articleAugust 2023
iETA: A Robust and Scalable Incremental Learning Framework for Time-of-Arrival Estimation
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4100–4111https://doi.org/10.1145/3580305.3599842Time-of-arrival estimation or Estimated Time of Arrival (ETA) has become an indispensable building block of modern intelligent transportation systems. While many efforts have been made for time-of-arrival estimation, most of them have scalability and ...
- short-paperJuly 2023
Behavior Modeling for Point of Interest Search
- Haitian Chen,
- Qingyao Ai,
- Zhijing Wu,
- Zhihong Wang,
- Yiqun Liu,
- Min Zhang,
- Shaoping Ma,
- Juan Hu,
- Naiqiang Tan,
- Hua Chai
SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information RetrievalJuly 2023, Pages 1843–1847https://doi.org/10.1145/3539618.3591955With the increasing popularity of location-based services, the point-of-interest (POI) search has received considerable attention in recent years. Existing studies on POI search mostly focus on how to construct better retrieval models to retrieve the ...
- research-articleMay 2023
Travel Time Distribution Estimation by Learning Representations Over Temporal Attributed Graphs
- Wanyi Zhou,
- Xiaolin Xiao,
- Yue-Jiao Gong,
- Jia Chen,
- Jun Fang,
- Naiqiang Tan,
- Nan Ma,
- Qun Li,
- Chai Hua,
- Sang-Woon Jeon,
- Jun Zhang
IEEE Transactions on Intelligent Transportation Systems (ITS-TRANSACTIONS), Volume 24, Issue 5May 2023, Pages 5069–5081https://doi.org/10.1109/TITS.2023.3247884Travel time estimation is a crucial task in practical transportation applications, while providing the reliability of estimation is important in many working scenarios. Most existing studies do not consider the dynamics of traffic status for different ...