Selected Publications:
Publication by date is available here and Publication by topic is available here
- City Simulation
- Mobility and Urban Science
- Computational Social Science
- Knowledge and Recommendation
- J. Feng, Z. Yang, F. Xu, H. Yu, M. Wang and Yong Li. Learning to Simulate Human Mobility, in KDD 2020 (ai for covid). (KDD) [Code]
- Q. Hao, L. Chen, F. Xu and Yong Li. Understanding the Urban Pandemic Spreading of COVID-19 with Real World Mobility Data, in KDD 2020 (ai for covid). (KDD) [Code]
- S. Song, Z. Zong, and Yong Li, X. Liu and Y. Yu. Reinforced Epidemic Control: Saving Both Lives and Economy, in KDD 2020 (ai for covid). (KDD) [Code]
- H. Shi, Q. Yao, Q. Guo, Y. Li, L. Zhang, J. Ye, Yong Li, Y. Liu. Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network, in ICDE 2020 (short paper). (ICDE)
- Z. Zong, J. Feng, K. Liu, H. Shi, Yong Li, F. Sun, A. Guo, D. Jin. DeepDPM: Dynamic Population Mapping via Deep Neural Network, in AAAI 2019. (AAAI)
- F. Xu, Yong Li, and S. Xu. Attentional Multi-graph Convolutional Network for Regional Economy Prediction with Open Migration Data, in KDD 2020 (research track). (KDD)
- J. Feng, Z. Yang, F. Xu, H. Yu, M. Wang and Yong Li. Learning to Simulate Human Mobility, in KDD 2020 (ai for covid). (KDD) [Code]
- Q. Hao, L. Chen, F. Xu and Yong Li. Understanding the Urban Pandemic Spreading of COVID-19 with Real World Mobility Data, in KDD 2020 (ai for covid). (KDD) [Code]
- S. Song, Z. Zong, and Yong Li, X. Liu and Y. Yu. Reinforced Epidemic Control: Saving Both Lives and Economy, in KDD 2020 (ai for covid). (KDD) [Code]
- C. Gao, C. Huang, D. Lin, Yong Li, and D. Jin. DPLCF: Differentially Private Local Collaborative Filtering, in SIGIR 2020 (long paper). (SIGIR)
- F. Xu, Z. Lin, D. Guo, and Yong Li. SUME: Semantic-enhanced Urban Mobility Network Embedding for User Demographic Inference, in ACM UbiComp 2020 (IMWUT). (UbiComp)
- Z. Chen, H. Cao, H. Wang, F. Xu, V. Kostakos, and Yong Li. Will You Come Back / Check-in Again? Understanding Characteristics Leading to Urban Revisitation and Re-check-in, in ACM UbiComp 2020 (IMWUT). (UbiComp)
- J. Feng, Z. Lin, T. Xia, F. Sun, D. Guo, and Yong Li. A Sequential Convolution Network for Population Flow Prediction with Explicitly Correlation Modelling, in IJCAI 2020. (IJCAI)
- M. Zhang, T. Li, Yong Li, and P. Hui. Multi-View Joint Graph Representation Learning for Urban Region Embedding, in IJCAI 2020. (IJCAI) [Code]
- D. Wu, T. Xiao, X. Liao, J. Luo, C. Wu, and Yong Li. When Sharing Economy Meets IoT: Towards Fine-grained Urban Air Quality Monitoring through Mobile Crowdsensing on Bike-share System, in ACM UbiComp 2020 (IMWUT). (UbiComp)
- T. Li, M. Zhang, H. Cao, Yong Li, S. Tarkoma and P. Hui. ”What Apps Did You Use?“: Understanding the Long-term Evolution of Mobile App Usage, in WWW 2020, long paper. (WWW)
- J. Feng, C. Rong, F. Sun, D. Guo, and Yong Li. PMF: A Privacy-preserving Human Mobility Prediction Framework via Federated Learning, in ACM UbiComp 2020 (IMWUT). (UbiComp)
- H. Shi, Q. Yao, Q. Guo, Y. Li, L. Zhang, J. Ye, Yong Li, Y. Liu. Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network, in ICDE 2020 (short paper). (ICDE)
- J. Ding, G. Yu, Yong Li, H. Gao, D. Jin. Learning from Hometown and Current City: POI Recommendation for Cross-city Travelers via Leveraging User Interest Drift and Transfer, in ACM UbiComp 2020 (IMWUT). (UbiComp)
- Y. Fan, Z. Tu, Yong Li, X. Chen, L. Zhang, L. Su, D. Jin. Personalized Context-aware Collaborative Online Activity Prediction, in ACM UbiComp 2020 (IMWUT). (UbiComp)
- H. Shi, C. Zhang, Q. Yao, Yong Li, F. Sun, D. Jin. State-Sharing Sparse Hidden Markov Models for Personalized Sequences, in KDD 2019, research track, oral paper. (KDD)
- T. Xia, Y. Yu, F. Xu, Yong Li. Understanding Urban Dynamics via State-sharing Hidden Markov Model, in WWW 2019, short paper. (WWW) [Code]
- F. Xu, Z. Tu, H. Huang, S. Chang, Yong Li. No More than What I Post: Preventing Linkage Attacks on Check-in Services, in WWW 2019, short paper. (WWW)
- M. Zhang, T. Li, H. Shi, Yong Li, H. Pan. A Decomposition Approach for Urban Anomaly Detection Across Spatiotemporal Data, in IJCAI 2019. (IJCAI)
- T. Xia, Yong Li. Revealing Urban Dynamics by Learning Online and Offline Behaviours Together, in ACM UbiComp 2019 (IMWUT). (UbiComp)
- C. Gao, C. Huang, Y. Yu, Yong Li, D. Jin. Privacy-preserving Cross-domain Location Recommendation, in ACM UbiComp 2019 (IMWUT). (UbiComp)
- Z. Tu, Y. Fan, Yong Li, X. Chen, L. Su, D. Jin. From Fingerprint to Footprint: Cold-start Location Recommendation by Learning User Interest from App Data, in ACM UbiComp 2019 (IMWUT). (UbiComp)
- H. Wang, Yong Li, S. Zeng, G. Wang, P. Zhang, P. Hui, D. Jin. Modeling Spatio-Temporal App Usage for a Large User Population, in ACM UbiComp 2019 (IMWUT). (UbiComp)
- X. Chen, Y. Wang, S. Pan, Yong Li, P. Zhang. CAP: Context-aware App-usage Prediction, in ACM UbiComp 2019 (IMWUT). (UbiComp)
- Z. Lin, J. Feng, Z. Lu, Yong Li, F. Sun, A. Guo, D. Jin. DeepSTN+: Context-aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis, in AAAI 2019. (AAAI)
- Z. Zong, J. Feng, K. Liu, H. Shi, Yong Li, F. Sun, A. Guo, D. Jin. DeepDPM: Dynamic Population Mapping via Deep Neural Network, in AAAI 2019. (AAAI)
- H. Cao, Z. Chen, Yong Li, V. Kostakos. Revisitation in Urban Space vs. Online: a Comparison Across POIs, Websites, and Smartphone Apps, in ACM UbiComp 2019 (IMWUT). (UbiComp)
- F. Xu, G. Zhang, J. Huang, Yong Li, D. Yang, Y. Zhao, F. Meng. Understanding Motivations behind Inaccurate Check-ins, in CSCW 2018. (CSCW)
- J. Zhang, C. Gao, D. Jin, Yong Li. Group-Buying Recommendation for Social E-Commerce, in ICDE 2021. (ICDE) [Code]
- F. Xu, G. Zhang, Y. Yuan, H. Huang, D. Yang, D. Jin, Yong Li. Would You Like to Join Us: Understanding the Invitation Acceptance in Agent-initiated Social E-commerce, in ICWSM 2021. (ICWSM)
- Z. Chen, H. Cao, F. Xu, M. Cheng, T Wang, and Yong Li. Understanding the Role of Intermediaries in Online Social E-commerces: an Exploratory Study of Beidian, in CSCW 2020. (CSCW)
- Z. Chen, H. Cao, H. Wang, F. Xu, V. Kostakos, and Yong Li. Will You Come Back / Check-in Again? Understanding Characteristics Leading to Urban Revisitation and Re-check-in, in ACM UbiComp 2020 (IMWUT). (UbiComp)
- T. Li, M. Zhang, H. Cao, Yong Li, S. Tarkoma and P. Hui. ”What Apps Did You Use?“: Understanding the Long-term Evolution of Mobile App Usage, in WWW 2020, long paper. (WWW)
- H. Cao, Z. Chen, F. Xu, T. Wang, Yong Li. When E-Commerce Meets Intimacy: An Empirical Study of Social Commerce Site Beidian, in ICWSM 2020. (ICWSM)
- F. Xu, Z. Han, J. Piao, Yong Li. "I Think You’ll Like It": Modelling the Online Purchase Behavior in Social E-commerce, in CSCW 2019. (CSCW)
- F. Xu, Z. Tu, H. Huang, S. Chang, Yong Li. No More than What I Post: Preventing Linkage Attacks on Check-in Services, in WWW 2019, short paper. (WWW)
- Y. Yan, Z. Li, A. Chen, C. Wilson, T. Xu, E. Zhai, Yong Li, Y. Liu. Understanding and Detecting Overlay-based Android Malware at Market Scales, in MobiSys 2019. (MobiSys) [Code]
- F. Xu, G. Zhang, J. Huang, Yong Li, D. Yang, Y. Zhao, F. Meng. Understanding Motivations behind Inaccurate Check-ins, in CSCW 2018. (CSCW)
- J. Zhang, C. Gao, D. Jin, Yong Li. Group-Buying Recommendation for Social E-Commerce, in ICDE 2021. (ICDE) [Code]
- J. Ding, Y. Quan, Q. Yao, Yong Li, D. Jin. Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering, in NeurIPS 2020. (NeurIPS) [Code]
- B. Jin, C. Gao, X. He, Yong Li, and D. Jin. Multi-behavior Recommendation with Graph Convolution Networks, in SIGIR 2020 (long paper). (SIGIR)
- J. Chang, C. Gao, X. He, Yong Li, and D. Jin. Bundle Recommendation with Graph Convolutional Networks, in SIGIR 2020 (short paper). (SIGIR) [Code]
- Y. Liu, Q. Yao and Yong Li. Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases, in WWW 2020, long paper. (WWW) [Code]
- Q. Yao, X. Chen, J. Kwok, Yong Li and C. Hsieh. Efficient One-shot Interaction Functions Search for Collaborative Filtering, in WWW 2020, long paper. (WWW) [Code]
- Y. Zheng, C. Gao, X. He, Yong Li, D. Jin. Incorporating Price into Recommender System, in ICDE 2020 (long paper). (ICDE)
- J. Ding, G. Yu, Yong Li, H. Gao, D. Jin. Learning from Hometown and Current City: POI Recommendation for Cross-city Travelers via Leveraging User Interest Drift and Transfer, in ACM UbiComp 2020 (IMWUT). (UbiComp)
- Y. Chen, B. Chen, X. He, C. Gao, Yong Li, J. Lou, Y. Wang. LambdaOpt: Learn to Regularize Recommender Models in Finer Levels, in KDD 2019, research track, oral paper. (KDD) [Code]
- J. Feng, M. Zhang, H. Wang, Z. Yang, C. Zhang, Yong Li, D. Jin. DPLink: User Identity Linkage via Deep Neural Network From Heterogeneous Mobility Data, in WWW 2019, long paper. (WWW) [Code]
- C. Gao, X. Chen, F. Feng, K. Zhao, X. He, Yong Li, D. Jin. Cross-domain Recommendation Without Sharing User-relevant Data, in WWW 2019, long paper. (WWW)
- J. Ding, Y. Quan, X. He, Yong Li, D. Jin. Reinforced Negative Sampling for Recommendation with Exposure Data, in IJCAI 2019. (IJCAI) [Code]
- H. Yan, X. Chen, C. Gao, Yong Li, D. Jin. DeepAPF: Deep Attentive Probabilistic Factorization for Multi-site Video Recommendation, in IJCAI 2019. (IJCAI)
- C. Gao, C. Huang, Y. Yu, Yong Li, D. Jin. Privacy-preserving Cross-domain Location Recommendation, in ACM UbiComp 2019 (IMWUT). (UbiComp)
- Z. Tu, Y. Fan, Yong Li, X. Chen, L. Su, D. Jin. From Fingerprint to Footprint: Cold-start Location Recommendation by Learning User Interest from App Data, in ACM UbiComp 2019 (IMWUT). (UbiComp)
- C. Gao, X. He, D. Gan, X. Chen, F. Feng, Yong Li, T. Chua, D. Jin. Neural Multi-task Recommendation from Multi-behavior Data, in ICDE 2019. (ICDE)