---2023---
- Adaptive Graph Neural Diffusion for Traffic Demand Forecasting. Yiling Wu, Xinfeng Zhang and Yaowei Wang. CIKM 2023. paper #traffic-demand-forecasting
- A Semi-Supervised Anomaly Network Traffic Detection Framework via Multimodal Traffic Information Fusion. Yu Zheng, Xinglin Lian, Zhangxuan Dang, Chunlei Peng, Chao Yang and Jianfeng Ma. CIKM 2023. paper #traffic-anomaly-detection
- An AI-based Simulation and Optimization Framework for Logistic Systems. Zefang Zong, Huan Yan, Hongjie Sui, Haoxiang Li Peiqi Jiang, Yong Li. CIKM 2023. paper #Logistic-systems
- Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank. Zhanyu Liu, Guanjie Zheng and Yanwei Yu. CIKM 2023. paper #traffic-forecasting
- CARPG: Cross-City Knowledge Transfer for Traffic Accident Prediction via Attentive Region-level Parameter Generation. Guang Yang, Yuequn Zhang, Jinquan Hang, Xinyue Feng, Zejun Xie, Desheng Zhang and Yu Yang. CIKM 2023. paper #traffic-accident-prediction
- CTCam: Enhancing Transportation Evaluation through Fusion of Cellular Traffic and Camera-Based Vehicle Flows. ChungYi Lin, Shen-Lung Tung, Hung-Ting Su and Winston H. Hsu. CIKM 2023. paper #transportation-evaluation
- DeepSTA: A Spatial-Temporal Attention Network for Logistics Delivery Timely Rate Prediction in Anomaly Conditions. Jinhui Yi, Huan Yan, Haotian Wang, Jian Yuan and Yong Li. CIKM 2023. paper #delivery-timely-rate-prediction
- DiffUFlow: Robust Fine-grained Urban Flow Inference with Denoising Diffusion Model. Yuhao Zheng, Lian Zhong, Senzhang Wang, Yu Yang, Weixi Gu, Junbo Zhang, and Jianxin Wang. CIKM 2023. paper #urban-flow-inference
- Enhancing Dynamic On-demand Food Order Dispatching via Future-informed and Spatial-temporal Extended Decisions. Yile Liang, Donghui Li, Jiuxia Zhao, Xuetao Ding, Huanjia Lian, Jinghua Hao and Renqing He. CIKM 2023. paper #food-order-dispatching
- Enhancing the Robustness via Adversarial Learning and Joint Spatial-temporal Embeddings in Traffic Forecasting. Juyong Jiang, Binqing Wu, Ling Chen, Kai Zhang and Sunghun Kim. CIKM 2023. paper #traffic-forecasting
- Enhancing Spatio-temporal Traffic Prediction through Urban Human Activity Analysis. Sumin Han, Youngjun Park, Minji Lee, Jisun An and Dongman Lee. CIKM 2023. paper #traffic-prediction
- Explainable Spatial-Temporal Graph Neural Networks. Jiabin Tang, Lianghao Xia and Chao Huang. CIKM 2023. paper #explainable #spatio-temporal-graph
- GBTTE: Graph Attention Network Based Bus Travel Time Estimation. Rong Yuecheng, Yao Juntao, Liu Jun, Fang Yifan, Luo Wei, Liu Hao, Ma Jie, Dan Zepeng, Lin Jinzhu, Wu Zhi, Zhang Yan and Zhang Chuanming. CIKM 2023. paper #travel-time-estimation
- HST-GT:Heterogeneous Spatial-Temporal Graph Transformer for Delivery Time Estimation in Warehouse-Distribution Integration E-Commerce. Xiaohui Zhao, Shuai Wang, Hai Wang, Tian He, Desheng Zhang and Guang Wang. CIKM 2023. paper #delivery-time-estimation #spatio-temporal-graph-transformer
- Hierarchical Information Enhanced Traffic Forecasting. Qian Ma, Zijian Zhang, Xiangyu Zhao, Haoliang Li, Hongwei Zhao, Yiqi Wang, Zitao Liu and Wanyu Wang. CIKM 2023. paper #traffic-prediction
- Mask- and Contrast-Enhanced Spatio-Temporal Learning for Urban Flow Prediction. Xu Zhang, Yongshun Gong, Xinxin Zhang, Xiaoming Wu, Chengqi Zhang and Xiangjun Dong. CIKM 2023. paper #urban-flow-prediction
- MLPST: MLP is All You Need for Spatio-Temporal Prediction. Zijian Zhang, Ze Huang, Zhiwei Hu, Xiangyu Zhao, Wanyu Wang, Zitao Liu, Junbo Zhang, S. Joe Qin and Hongwei Zhao. CIKM 2023. paper #spatio-temporal-prediction
- MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation. Zekun Cai, Renhe Jiang, Xinyu Yang, Zhaonan Wang, Diansheng Guo, Hiroki Kobayashi, Xuan Song and Ryosuke Shibasaki. CIKM 2023. paper #urban-time-series-forecasting
- ParkFlow: Intelligent Dispersal for Mitigating Parking Shortages Using Multi-Granular Spatial-Temporal Analysis. Yang Fan Chiang, Chun-Wei Shen, Jhe-Wei Tsai, Pei-Xuan Li, Tzu-Chang Lee and Hsun-Ping Hsieh. CIKM 2023. paper #multi-granular-spatial-temporal-analysis
- PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction. Zijian Zhang, Xiangyu Zhao, Qidong Liu, Chunxu Zhang, Qian Ma, Wanyu Wang, Hongwei Zhao, Yiqi Wang and Zitao Liu. CIKM 2023. paper #spatio-temporal-prediction
- Region Profile Enhanced Urban Spatio-Temporal Prediction via Adaptive Meta Learning. Jie Chen, Tong Liu and Ruiyuan Li. CIKM 2023. paper #spatio-temporal-prediction
- Region-Wise Attentive Multi-View Representation Learning for Urban Region Embedding. Weiliang Chen and Qianqian Ren. CIKM 2023. paper #urban-region-embedding
- STREAMS: Towards Spatio-Temporal Causal Discovery with Reinforcement Learning for Streamflow Rate Prediction. Paras Sheth, Ahmadreza Mosallanezhad, Kaize Ding, Reepal Shah, John Sabo, Huan Liu and K. Selçuk Candan. CIKM 2023. paper #spatio-temporal-causal-discovery
- STAMINA (Spatial-Temporal Aligned Meteorological INformation Attention) and FPL (Focal Precip Loss): Advancements in Precipitation Nowcasting for Heavy Rainfall Events. Ping-Chia Huang, Yueh-Li Chen, Yi-Syuan Liou, Bing-Chen Tsai, Chun-Chieh Wu and Winston H. Hsu. CIKM 2023. paper #preciptation-nowcasting
- ST-MoE: Spatio-Temporal Mixture-of-Experts for Debiasing in Traffic Prediction. huhao Li, Yue Cui, Yan Zhao, Ruiyuan Zhang, Weidong Yang and Xiaofang Zhou. CIKM 2023. paper #traffic-prediction
- Spatial-temporal Graph Boosting Network: Enhancing Spatial-temporal Graph Neural Networks via Gradient Boosting. Yujie Fan, Chin-Chia Michael Yeh, Huiyuan Chen, Yan Zheng, Liang Wang, Junpeng Wang, Xin Dai, Zhongfang Zhuang and Wei Zhang. CIKM 2023. paper #spatio-temporal-graph
- Spatio-Temporal Meta Contrastive Learning. Jiabin Tang, Lianghao Xia, Jie Hu and Chao Huang. CIKM 2023. paper #spatio-temporal #contrastive-learning
- STGIN: Spatial-Temporal Graph Interaction Network for large-scale POI recommendation. Shaohua Liu, Yu Qi, Gen Li, Mingjian Chen, Teng Zhang, Jia Cheng and Jun Lei. CIKM 2023. paper #POI-recommendation
- Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting. Hangchen Liu, Zheng Dong, Renhe Jiang, Jiewen Deng, Jinliang Deng, Quanjun Chen and Xuan Song. CIKM 2023. paper #traffic-forecasting
- STRAP: A Spatio-Temporal Framework for Real Estate Apprisal. Hojoon Lee, Hawon Jeong, Byungkun Lee, Kyungyup Daniel Lee and Jaegul Choo. CIKM 2023. paper #spatio-temporal
- Urban-scale POI Updating with Crowd Intelligence. Zhiqing Hong, Haotian Wang, Wenjun Lyu, Hai Wang, Yunhuai Liu, Guang Wang, Tian He and Desheng Zhang. CIKM 2023. paper #POI-updating
- UrbanFloodKG: An Urban Flood Knowledge Graph System for Risk Assessment. Yu Wang, Feng Ye, Binquan Li, Gaoyang Jin, Dong Xu and Fengsheng Li. CIKM 2023. paper #urban-konwledge-graph
- Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction. Xinke Jiang, Dingyi Zhuang, Xianghui Zhang, Hao Chen, Jiayuan Luo, and Xiaowei Gao. CIKM 2023. paper #uncertainty-quantification #travel-demand-prediction
---2020---
A Reproducibility Study of Deep and Surface Machine Learning Methods for Human-related Trajectory Prediction. Bardh Prenkaj, Paola Velardi, Damiano Distante, Stefano Faralli. CIKM2020. [paper]
A Joint Inverse Reinforcement Learning and Deep Learning Model for Drivers' Behavioral Prediction. Guojun Wu, Yanhua Li, Shikai Luo, Ge Song, Qichao Wang, Jing He, Jieping Ye, Xiaohu Qie, Hongtu Zhu. CIKM2020. [paper]
Deep Spatio-Temporal Multiple Domain Fusion Network for Urban Anomalies Detection. Ruiqiang Liu, Shuai Zhao, Bo Cheng, Hao Yang, Haina Tang, Taoyu Li. CIKM2020. [paper]
Deep Graph Convolutional Networks for Incident-Driven Traffic Speed Prediction. Qinge Xie, Tiancheng Guo, Yang Chen, Yu Xiao, Xin Wang, Ben Y. Zhao. CIKM2020. [paper]
DATSING: Data Augmented Time Series Forecasting with Adversarial Domain Adaptation. Hailin Hu, MingJian Tang, Chengcheng Bai. CIKM2020. [paper]
Elevated Road Network: A Metric Learning Method for Recognizing Whether a Vehicle is on an Elevated Road. Xiaobing Zhang, Hailiang Xu, Jian Yang, Jia Sun, Fan Chen, Leiyun Li. CIKM2020. [paper]
GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning. Huichu Zhang, Chang Liu, Weinan Zhang, Guanjie Zheng, Yong Yu. CIKM2020. [paper]
Generating Full Spatiotemporal Vehicular Paths: A Data Fusion Approach. Nan Xiao, Nan Hu, Liang Yu, Cheng Long. CIKM2020. [paper]
Imbalanced Time Series Classification for Flight Data Analyzing with Nonlinear Granger Causality Learning. Hao Huang, Chenxiao Xu, Shinjae Yoo, Weizhong Yan, Tianyi Wang, Feng Xue. CIKM2020. [paper]
Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network. Can Li, Lei Bai, Wei Liu, Lina Yao, S. Travis Waller. CIKM2020. [paper]
Learning Graph-Based Geographical Latent Representation for Point-of-Interest Recommendation. Buru Chang, Gwanghoon Jang, Seoyoon Kim, Jaewoo Kang. CIKM2020. [paper]
Multi-task Adversarial Spatial-Temporal Networks for Crowd Flow Prediction. Senzhang Wang, Hao Miao, Hao Chen, Zhiqiu Huang. CIKM2020. [paper]
Magellan: A Personalized Travel Recommendation System Using Transaction Data. Konik Kothari, Dhruv Gelda, Wei Zhang, Hao Yang. CIKM2020. [paper]
STP-UDGAT: Spatial-Temporal-Preference User Dimensional Graph Attention Network for Next POI Recommendation. Nicholas Lim, Bryan Hooi, See-Kiong Ng, Xueou Wang, Yong Liang Goh, Renrong Weng, Jagannadan Varadarajan. CIKM2020. [paper]
Spatiotemporal Adaptive Gated Graph Convolution Network for Urban Traffic Flow Forecasting. Bin Lu, Xiaoying Gan, Haiming Jin, Luoyi Fu, Haisong Zhang. CIKM2020. [paper]
STP-TrellisNets: Spatial-Temporal Parallel TrellisNets for Metro Station Passenger Flow Prediction. Junjie Ou, Jiahui Sun, Yichen Zhu, Haiming Jin, Yijuan Liu, Fan Zhang, Jianqiang Huang, Xinbing Wang. CIKM2020. [paper]
ST-GRAT: A Novel Spatio-temporal Graph Attention Networks for Accurately Forecasting Dynamically Changing Road Speed. Cheonbok Park, Chunggi Lee, Hyojin Bahng, Yunwon Tae, Seungmin Jin, Kihwan Kim, Sungahn Ko, Jaegul Choo. CIKM2020. [paper]
Spatial-Temporal Convolutional Graph Attention Networks for Citywide Traffic Flow Forecasting. Xiyue Zhang, Chao Huang, Yong Xu, Lianghao Xia. CIKM2020. [paper]
You Are How You Use: Catching Gas Theft Suspects among Diverse Restaurant Users. Xiaodu Yang, Xiuwen Yi, Shun Chen, Sijie Ruan, Junbo Zhang, Yu Zheng, Tianrui Li. CIKM2020. [paper]
---2019---
CityTraffic: Modeling Citywide Traffic via Neural Memorization and Generalization Approach. Xiuwen Yi, Zhewen Duan, Ting Li, Tianrui Li, Junbo Zhang, Yu Zheng. CIKM 2019. [paper]
DeepIST: Deep Image-based Spatio-Temporal Network for Travel Time Estimation. Tao-Yang Fu, Wang-Chien Lee. CIKM 2019. [paper]
Exploring The Interaction Effects for Temporal Spatial Behavior Prediction. Huan Yang, Tianyuan Liu, Yuqing Sun, Elisa Bertino. CIKM 2019. [paper]
Learning to Effectively Estimate the Travel Time for Fastest Route Recommendation. Ning Wu, Jingyuan Wang, Wayne Xin Zhao, Yang Jin. CIKM 2019. [paper]
Learning Region Similarity over Spatial Knowledge Graphs with Hierarchical Types and Semantic Relations. Xiongnan Jin, Byungkook Oh, Sanghak Lee, Dongho Lee, Kyong-Ho Lee, Liang Chen. CIKM 2019. [paper]
Matrix Factorization for Spatio-Temporal Neural Networks with Applications to Urban Flow Prediction. Zheyi Pan, Zhaoyuan Wang, Weifeng Wang, Yong Yu, Junbo Zhang, Yu Zheng. CIKM 2019. [paper]
Modeling temporal-spatial correlations for crime prediction. Xiangyu Zhao, Jiliang Tang. CIKM 2019. [paper]
Personalized Route Description Based On Historical Trajectories. Han Su, Guanglin Cong, Wei Chen, Bolong Zheng, Kai Zheng. CIKM 2019. [paper]
Query processing techniques for big spatial-keyword data. Ahmed R. Mahmood, Walid G. Aref. CIKM 2019. [paper]
Spatio-Temporal Graph Convolutional and Recurrent Networks for Citywide Passenger Demand Prediction. Lei Bai, Lina Yao, Salil S. Kanhere, Xianzhi Wang, Wei Liu, Zheng Yang. CIKM 2019. [paper]
STAR: Spatio-Temporal Taxonomy-Aware Tag Recommendation for Citizen Complaints. Jingyue Gao, Yuanduo He, Yasha Wang, Xiting Wang, Jiangtao Wang, Guangju Peng, Xu Chu. CIKM 2019. [paper]
Towards explainable representation of time-evolving graphs via spatial-temporal graph attention networks. Zhining Liu, Dawei Zhou, Jingrui He. CIKM 2019. [paper]
Temporal network embedding with micro-and macro-dynamics. Yuanfu Lu, Xiao Wang, Chuan Shi, Philip S. Yu, Yanfang Ye. CIKM 2019. [paper]
Unsupervised Representation Learning of Spatial Data via Multimodal Embedding. Porter Jenkins, Ahmad Farag, Suhang Wang, Zhenhui Li. CIKM 2019. [paper]
---2018---
Ontop-temporal: A Tool for Ontology-based Query Answering over Temporal Data. Elem Güzel Kalayci, Guohui Xiao, Vladislav Ryzhikov, Tahir Emre Kalayci, Diego Calvanese. CIKM 2018. [paper]
Traffic-cascade: Mining and visualizing lifecycles of traffic congestion events using public bus trajectories. Agus Trisnajaya Kwee, Meng-Fen Chiang, Philips Kokoh Prasetyo, Ee-Peng Lim. CIKM 2018. [paper]
Tequila: Temporal question answering over knowledge bases. Zhen Jia, Abdalghani Abujabal, Rishiraj Saha Roy, Jannik Strötgen, Gerhard Weikum. CIKM 2018. [paper]
---2017---
Destination-aware task assignment in spatial crowdsourcing. Yan Zhao, Yang Li, Yu Wang, Han Su, Kai Zheng. CIKM 2017. [paper]
Spatial crowdsourcing: Challenges, techniques, and applications. Yongxin Tong, Lei Chen, Cyrus Shahabi. CIKM 2017. [paper]
Urbanity: A System for Interactive Exploration of Urban Dynamics from Streaming Human Sensing Data. Mengxiong Liu, Zhengchao Liu, Chao Zhang, Keyang Zhang, Quan Yuan, Tim Hanratty, Jiawei Han. CIKM 2017. [paper]