Junbo Zhang

Orcid: 0000-0001-5947-1374

Affiliations:
  • JD.com


According to our database1, Junbo Zhang authored at least 122 papers between 2010 and 2025.

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Bibliography

2025
GeoMAE: Masking Representation Learning for Spatio-Temporal Graph Forecasting with Missing Values.
CoRR, August, 2025

Burst-Sensitive Traffic Forecast via Multi-Property Personalized Fusion in Federated Learning.
IEEE Trans. Mob. Comput., July, 2025

Daily Schedule Recommendation in Urban Life Based on Deep Reinforcement Learning.
IEEE Trans. Neural Networks Learn. Syst., February, 2025

Improving Open-world Continual Learning under the Constraints of Scarce Labeled Data.
CoRR, February, 2025

Enhancing cross-city spatio-temporal prediction via dynamic multi-scale hypergraph learning with domain adversarial training.
Knowl. Based Syst., 2025

Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook.
Inf. Fusion, 2025

Pre-training Enhanced Transformer for multivariate time series anomaly detection.
Inf. Fusion, 2025

Enhancing few-sample spatio-temporal prediction via relational fusion-based hypergraph neural network.
Inf. Fusion, 2025

Adversarial Transfer Learning-Based Hybrid Recurrent Network for Air Quality Prediction.
Int. J. Intell. Syst., 2025

Non-collective Calibrating Strategy for Time Series Forecasting.
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
Cross-Regional Fraud Detection via Continual Learning With Knowledge Transfer.
IEEE Trans. Knowl. Data Eng., December, 2024

Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey.
IEEE Trans. Knowl. Data Eng., October, 2024

Exploring the Distributed Knowledge Congruence in Proxy-data-free Federated Distillation.
ACM Trans. Intell. Syst. Technol., April, 2024

Federated Continual Learning via Knowledge Fusion: A Survey.
IEEE Trans. Knowl. Data Eng., 2024

Multi-scale feature enhanced spatio-temporal learning for traffic flow forecasting.
Knowl. Based Syst., 2024

UMOD: A Novel and Effective Urban Metro Origin-Destination Flow Prediction Method.
CoRR, 2024

Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook.
CoRR, 2024

Personalized Federated Continual Learning via Multi-Granularity Prompt.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Spatio-Temporal Consistency Enhanced Differential Network for Interpretable Indoor Temperature Prediction.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

The 4th KDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (DeepSpatial'24).
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

GSDI: Spatio-Temporal Contrastive Learning for Geo-Sensory Data Inference.
Proceedings of the International Joint Conference on Neural Networks, 2024

2023
HiSTGNN: Hierarchical spatio-temporal graph neural network for weather forecasting.
Inf. Sci., November, 2023

Spatio-Temporal Dynamic Graph Relation Learning for Urban Metro Flow Prediction.
IEEE Trans. Knowl. Data Eng., October, 2023

Mixed-Order Relation-Aware Recurrent Neural Networks for Spatio-Temporal Forecasting.
IEEE Trans. Knowl. Data Eng., September, 2023

Forecasting Fine-Grained Urban Flows Via Spatio-Temporal Contrastive Self-Supervision.
IEEE Trans. Knowl. Data Eng., August, 2023

Fine-Grained Urban Flow Inference With Incomplete Data.
IEEE Trans. Knowl. Data Eng., June, 2023

Shortening Passengers' Travel Time: A Dynamic Metro Train Scheduling Approach Using Deep Reinforcement Learning.
IEEE Trans. Knowl. Data Eng., May, 2023

Cross-Domain Knowledge Graph Chiasmal Embedding for Multi-Domain Item-Item Recommendation.
IEEE Trans. Knowl. Data Eng., May, 2023

AutoSTG<sup>+</sup>: An automatic framework to discover the optimal network for spatio-temporal graph prediction.
Artif. Intell., May, 2023

Urban Flow Pattern Mining Based on Multi-Source Heterogeneous Data Fusion and Knowledge Graph Embedding.
IEEE Trans. Knowl. Data Eng., 2023

TrajMesa: A Distributed NoSQL-Based Trajectory Data Management System.
IEEE Trans. Knowl. Data Eng., 2023

Housing rental suggestion based on e-commerce data.
Knowl. Based Syst., 2023

Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey.
CoRR, 2023

DiffUFlow: Robust Fine-grained Urban Flow Inference with Denoising Diffusion Model.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

MLPST: MLP is All You Need for Spatio-Temporal Prediction.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

AutoSTL: Automated Spatio-Temporal Multi-Task Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

AirFormer: Predicting Nationwide Air Quality in China with Transformers.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Win-Win: A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Gas-Theft Suspect Detection Among Boiler Room Users: A Data-Driven Approach.
IEEE Trans. Knowl. Data Eng., 2022

Predicting Citywide Crowd Flows in Irregular Regions Using Multi-View Graph Convolutional Networks.
IEEE Trans. Knowl. Data Eng., 2022

Spatio-Temporal Meta Learning for Urban Traffic Prediction.
IEEE Trans. Knowl. Data Eng., 2022

Introduction to the Special Issue on Deep Learning for Spatio-Temporal Data: Part 2.
ACM Trans. Intell. Syst. Technol., 2022

Predicting Fine-Grained Air Quality Based on Deep Neural Networks.
IEEE Trans. Big Data, 2022

Federated Forest.
IEEE Trans. Big Data, 2022

Fairness and accuracy in horizontal federated learning.
Inf. Sci., 2022

A Cross-City Federated Transfer Learning Framework: A Case Study on Urban Region Profiling.
CoRR, 2022

Precision CityShield Against Hazardous Chemicals Threats via Location Mining and Self-Supervised Learning.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

DeepSpatial'22: The 3rd International Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Efficient Spatio-Temporal Randomly Wired Neural Networks for Traffic Forecasting.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

Multi-memory Enhanced Separation Network for Indoor Temperature Prediction.
Proceedings of the Database Systems for Advanced Applications, 2022

Generative-Free Urban Flow Imputation.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

TrajFormer: Efficient Trajectory Classification with Transformers.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
ACM TIST Special Issue on Deep Learning for Spatio-Temporal Data: Part 1.
ACM Trans. Intell. Syst. Technol., 2021

Multi-source information fusion based on rough set theory: A review.
Inf. Fusion, 2021

Federated Digital Gateway: Methodologies, Tools, and Applications.
IEEE Intell. Syst., 2021

AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph✱.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Fine-Grained Urban Flow Prediction.
Proceedings of the WWW '21: The Web Conference 2021, 2021

POI Alias Discovery in Delivery Addresses using User Locations.
Proceedings of the SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems, 2021

Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Flow Prediction in Spatio-Temporal Networks Based on Multitask Deep Learning.
IEEE Trans. Knowl. Data Eng., 2020

Urban flow prediction from spatiotemporal data using machine learning: A survey.
Inf. Fusion, 2020

Predicting and ranking box office revenue of movies based on big data.
Inf. Fusion, 2020

Fairness and Accuracy in Federated Learning.
CoRR, 2020

ReAD: A Regional Anomaly Detection Framework Based on Dynamic Partition.
CoRR, 2020

Revisiting Convolutional Neural Networks for Urban Flow Analytics.
CoRR, 2020

Federated Extra-Trees with Privacy Preserving.
CoRR, 2020

Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

You Are How You Use: Catching Gas Theft Suspects among Diverse Restaurant Users.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019
CityGuard: Citywide Fire Risk Forecasting Using A Machine Learning Approach.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2019

Urban flows prediction from spatial-temporal data using machine learning: A survey.
CoRR, 2019

Federated Forest.
CoRR, 2019

Predicting Citywide Crowd Flows in Irregular Regions Using Multi-View Graph Convolutional Networks.
CoRR, 2019

Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

UrbanFM: Inferring Fine-Grained Urban Flows.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

CityTraffic: Modeling Citywide Traffic via Neural Memorization and Generalization Approach.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Matrix Factorization for Spatio-Temporal Neural Networks with Applications to Urban Flow Prediction.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
HyperST-Net: Hypernetworks for Spatio-Temporal Forecasting.
CoRR, 2018

Predicting citywide crowd flows using deep spatio-temporal residual networks.
Artif. Intell., 2018

Deep Distributed Fusion Network for Air Quality Prediction.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

DeepCrime: Attentive Hierarchical Recurrent Networks for Crime Prediction.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

When Will You Arrive? Estimating Travel Time Based on Deep Neural Networks.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
J2M: a Java to MapReduce translator for cloud computing.
J. Supercomput., 2016

Efficient parallel boolean matrix based algorithms for computing composite rough set approximations.
Inf. Sci., 2016

Incremental updating of rough approximations in interval-valued information systems under attribute generalization.
Inf. Sci., 2016

Parallel Large-Scale Attribute Reduction on Cloud Systems.
CoRR, 2016

ST-MVL: Filling Missing Values in Geo-Sensory Time Series Data.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

DNN-based prediction model for spatio-temporal data.
Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31, 2016

2015
A Parallel Matrix-Based Method for Computing Approximations in Incomplete Information Systems.
IEEE Trans. Knowl. Data Eng., 2015

Incremental updating approximations in probabilistic rough sets under the variation of attributes.
Knowl. Based Syst., 2015

Parallel computing of approximations in dominance-based rough sets approach.
Knowl. Based Syst., 2015

不同MapReduce运行系统的性能测试与分析 (Performance Testing and Analysis among Different MapReduce Runtime Systems).
计算机科学, 2015

A fuzzy rough set approach for incremental feature selection on hybrid information systems.
Fuzzy Sets Syst., 2015

PICKT: A Solution for Big Data Analysis.
Proceedings of the Rough Sets and Knowledge Technology - 10th International Conference, 2015

2014
Composite rough sets for dynamic data mining.
Inf. Sci., 2014

A comparison of parallel large-scale knowledge acquisition using rough set theory on different MapReduce runtime systems.
Int. J. Approx. Reason., 2014

A rough set-based incremental approach for learning knowledge in dynamic incomplete information systems.
Int. J. Approx. Reason., 2014

Incremental Maintenance of Rough Fuzzy Set Approximations under the Variation of Object Set.
Fundam. Informaticae, 2014

2013
A Parallel Implementation of Computing Composite Rough Set Approximations on GPUs.
Proceedings of the Rough Sets and Knowledge Technology - 8th International Conference, 2013

A Fuzzy Rough Set Approach for Incrementally Updating Approximations in Hybrid Information Systems.
Proceedings of the Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, 2013

PLAR: Parallel Large-Scale Attribute Reduction on Cloud Systems.
Proceedings of the International Conference on Parallel and Distributed Computing, 2013

H2T: A Simple Hadoop-to-Twister Translator for Cloud Computing.
Proceedings of the International Symposium on Biometrics and Security Technologies, 2013

An incremental approach for updating approximations of rough fuzzy set under the variation of attribute values.
Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, 2013

2012
Rough Sets Based Incremental Rule Acquisition in Set-Valued Information Systems.
Proceedings of the Autonomous Systems: Developments and Trends, 2012

A parallel method for computing rough set approximations.
Inf. Sci., 2012

Neighborhood rough sets for dynamic data mining.
Int. J. Intell. Syst., 2012

Rough sets based matrix approaches with dynamic attribute variation in set-valued information systems.
Int. J. Approx. Reason., 2012

An Incremental Approach for Updating Approximations of Rough Fuzzy Sets under the Variation of the Object Set.
Proceedings of the Rough Sets and Current Trends in Computing, 2012

Parallel rough set based knowledge acquisition using MapReduce from big data.
Proceedings of the 1st International Workshop on Big Data, 2012

Composite Rough Sets.
Proceedings of the Artificial Intelligence and Computational Intelligence, 2012

2011
Incremental learning optimization on knowledge discovery in dynamic business intelligent systems.
J. Glob. Optim., 2011

Neighborhood Rough Sets Based Matrix Approach for Calculation of the Approximations.
Proceedings of the Rough Sets and Knowledge Technology - 6th International Conference, 2011

2010
A new method for calculation of the approximations under the probabilistic rough sets.
Proceedings of the 2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering, 2010

An approach for incremental updating approximations in Variable precision rough sets while attribute generalized.
Proceedings of the 2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering, 2010

Approaches for dynamically updating set approximations in dominance based rough sets while condition attributes value coarsening and refining.
Proceedings of the 2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering, 2010

A Method for Incremental Updating Approximations Based on Variable Precision Set-Valued Ordered Information Systems.
Proceedings of the 2010 IEEE International Conference on Granular Computing, 2010

A Method for Incremental Updating Approximations when Objects and Attributes Vary with Time.
Proceedings of the 2010 IEEE International Conference on Granular Computing, 2010


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