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ORCIDGao Cong
丛高
Person information
- unicode name: 丛高
- affiliation: Nanyang Technological University, Singapore
- affiliation: Aalborg University, Department of Computer Science, Denmark
- affiliation: Microsoft Research Asia
- affiliation: University of Edinburgh, School of Informatics, UK
- affiliation: National University of Singapore, Department of Computer Science
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2020 – today
- 2023
[j77]Shang Liu
, Gao Cong, Kaiyu Feng, Wanli Gu, Fuzheng Zhang:
Effectiveness Perspectives and a Deep Relevance Model for Spatial Keyword Queries. Proc. ACM Manag. Data 1(1): 11:1-11:25 (2023)- [j76]Tu Gu, Kaiyu Feng, Gao Cong, Cheng Long, Zheng Wang, Sheng Wang:
The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data. Proc. ACM Manag. Data 1(1): 63:1-63:26 (2023) - [j75]Pasquale Balsebre, Dezhong Yao, Gao Cong, Weiming Huang, Zhen Hai:
Mining Geospatial Relationships from Text. Proc. ACM Manag. Data 1(1): 93:1-93:26 (2023) - [j74]Yufan Sheng, Xin Cao, Yixiang Fang, Kaiqi Zhao, Jianzhong Qi, Gao Cong, Wenjie Zhang:
WISK: A Workload-aware Learned Index for Spatial Keyword Queries. Proc. ACM Manag. Data 1(2): 187:1-187:27 (2023) - [j73]Jiangneng Li, Zheng Wang, Gao Cong, Cheng Long, Han Mao Kiah, Bin Cui:
Towards Designing and Learning Piecewise Space-Filling Curves. Proc. VLDB Endow. 16(9): 2158-2171 (2023) - [j72]Zheng Wang, Cheng Long, Gao Cong:
Similar Sports Play Retrieval With Deep Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 35(4): 4253-4266 (2023) - [j71]Liang Zhang, Cheng Long, Gao Cong:
Region Embedding With Intra and Inter-View Contrastive Learning. IEEE Trans. Knowl. Data Eng. 35(9): 9031-9036 (2023) - [c141]Qianru Zhang, Zheng Wang, Cheng Long, Chao Huang, Siu-Ming Yiu, Yiding Liu, Gao Cong, Jieming Shi:
Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning. ICDE 2023: 246-258 - [c140]Shuai Liu, Xiucheng Li, Gao Cong, Yile Chen, Yue Jiang:
Multivariate Time-series Imputation with Disentangled Temporal Representations. ICLR 2023 - [c139]Yi Li, Weiming Huang, Gao Cong, Hao Wang, Zheng Wang:
Urban Region Representation Learning with OpenStreetMap Building Footprints. KDD 2023: 1363-1373 - [i28]Daniel Rugeles, Zhen Hai, Juan Felipe Carmona, Manoranjan Dash, Gao Cong:
Improving the Inference of Topic Models via Infinite Latent State Replications. CoRR abs/2301.12974 (2023) - [i27]Yufan Sheng, Xin Cao, Yixiang Fang, Kaiqi Zhao, Jianzhong Qi, Gao Cong, Wenjie Zhang:
WISK: A Workload-aware Learned Index for Spatial Keyword Queries. CoRR abs/2302.14287 (2023) - [i26]Gengchen Mai, Weiming Huang, Jin Sun, Suhang Song, Deepak Mishra, Ninghao Liu, Song Gao, Tianming Liu, Gao Cong, Yingjie Hu, Chris Cundy, Ziyuan Li, Rui Zhu, Ni Lao:
On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence. CoRR abs/2304.06798 (2023) - 2022
- [j70]Sheng Wang, Zhifeng Bao, J. Shane Culpepper, Gao Cong:
A Survey on Trajectory Data Management, Analytics, and Learning. ACM Comput. Surv. 54(2): 39:1-39:36 (2022) - [j69]Yue Zhao, Gao Cong, Jiachen Shi, Chunyan Miao:
QueryFormer: A Tree Transformer Model for Query Plan Representation. Proc. VLDB Endow. 15(8): 1658-1670 (2022) - [j68]Junghoon Kim, Kaiyu Feng, Gao Cong, Diwen Zhu, Wenyuan Yu, Chunyan Miao:
ABC: Attributed Bipartite Co-clustering. Proc. VLDB Endow. 15(10): 2134-2147 (2022) - [j67]Yue Chen, Kaiyu Feng, Gao Cong, Han Mao Kiah:
Example-based Spatial Pattern Matching. Proc. VLDB Endow. 15(11): 2572-2584 (2022) - [j66]Jiachen Shi, Gao Cong, Xiaoli Li:
Learned Index Benefits: Machine Learning Based Index Performance Estimation. Proc. VLDB Endow. 15(13): 3950-3962 (2022) - [j65]Hui Luo, Zhifeng Bao, Gao Cong, J. Shane Culpepper, Nguyen Lu Dang Khoa:
Let Trajectories Speak Out the Traffic Bottlenecks. ACM Trans. Intell. Syst. Technol. 13(1): 8:1-8:21 (2022) - [j64]Guangtao Wang, Gao Cong, Ying Zhang, Zhen Hai, Jieping Ye:
A Synopsis Based Approach for Itemset Frequency Estimation over Massive Multi-Transaction Stream. ACM Trans. Knowl. Discov. Data 16(2): 29:1-29:30 (2022) - [j63]Kaiqi Zhao, Gao Cong, Xiucheng Li:
PGeoTopic: A Distributed Solution for Mining Geographical Topic Models. IEEE Trans. Knowl. Data Eng. 34(2): 881-893 (2022) - [j62]Daniel Rugeles, Zhen Hai, Manoranjan Dash, Gao Cong:
Deterministic Inference of Topic Models via Maximal Latent State Replication. IEEE Trans. Knowl. Data Eng. 34(4): 1684-1695 (2022) - [j61]Di Yao, Gao Cong, Chao Zhang, Xuying Meng, Rongchang Duan, Jingping Bi:
A Linear Time Approach to Computing Time Series Similarity Based on Deep Metric Learning. IEEE Trans. Knowl. Data Eng. 34(10): 4554-4571 (2022) - [j60]Shengnan Guo, Youfang Lin, Huaiyu Wan, Xiucheng Li, Gao Cong:
Learning Dynamics and Heterogeneity of Spatial-Temporal Graph Data for Traffic Forecasting. IEEE Trans. Knowl. Data Eng. 34(11): 5415-5428 (2022) - [c138]Zizhong Meng, Peizhi Wu, Gao Cong, Rong Zhu, Shuai Ma:
Unsupervised Selectivity Estimation by Integrating Gaussian Mixture Models and an Autoregressive Model. EDBT 2022: 2:247-2:259 - [c137]Di Yao, Haonan Hu, Lun Du, Gao Cong, Shi Han, Jingping Bi:
TrajGAT: A Graph-based Long-term Dependency Modeling Approach for Trajectory Similarity Computation. KDD 2022: 2275-2285 - [c136]Dezhong Yao, Yuhong Gu, Gao Cong, Hai Jin, Xinqiao Lv:
Entity Resolution with Hierarchical Graph Attention Networks. SIGMOD Conference 2022: 429-442 - [c135]Junghoon Kim, Siqiang Luo, Gao Cong, Wenyuan Yu:
DMCS : Density Modularity based Community Search. SIGMOD Conference 2022: 889-903 - [c134]Jingyi Yang, Peizhi Wu, Gao Cong, Tieying Zhang, Xiao He:
SAM: Database Generation from Query Workloads with Supervised Autoregressive Models. SIGMOD Conference 2022: 1542-1555 - [c133]Jin Yao Chin, Yile Chen, Gao Cong:
The Datasets Dilemma: How Much Do We Really Know About Recommendation Datasets? WSDM 2022: 141-149 - [c132]Pasquale Balsebre, Dezhong Yao, Gao Cong, Zhen Hai:
Geospatial Entity Resolution. WWW 2022: 3061-3070 - [i25]Yile Chen, Xiucheng Li, Gao Cong, Cheng Long, Zhifeng Bao, Shang Liu, Wanli Gu, Fuzheng Zhang:
Points-of-Interest Relationship Inference with Spatial-enriched Graph Neural Networks. CoRR abs/2202.13686 (2022) - [i24]Junghoon Kim, Siqiang Luo, Gao Cong, Wenyuan Yu:
DMCS : Density Modularity based Community Search. CoRR abs/2204.07720 (2022) - [i23]Tiantian He, Haicang Zhou, Yew-Soon Ong, Gao Cong:
Not All Neighbors Are Worth Attending to: Graph Selective Attention Networks for Semi-supervised Learning. CoRR abs/2210.07715 (2022) - [i22]Qianru Zhang, Zheng Wang, Cheng Long, Chao Huang, Siu-Ming Yiu, Yiding Liu, Gao Cong, Jieming Shi:
Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning. CoRR abs/2211.08415 (2022) - [i21]Liang Zhang, Cheng Long, Gao Cong:
Region Embedding with Intra and Inter-View Contrastive Learning. CoRR abs/2211.08975 (2022) - 2021
- [j59]Yile Chen, Xiucheng Li, Gao Cong, Cheng Long, Zhifeng Bao, Shang Liu, Wanli Gu, Fuzheng Zhang:
Points-of-Interest Relationship Inference with Spatial-enriched Graph Neural Networks. Proc. VLDB Endow. 15(3): 504-512 (2021) - [j58]Yuxing Han, Ziniu Wu, Peizhi Wu, Rong Zhu, Jingyi Yang, Liang Wei Tan, Kai Zeng, Gao Cong, Yanzhao Qin, Andreas Pfadler, Zhengping Qian, Jingren Zhou, Jiangneng Li, Bin Cui:
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation. Proc. VLDB Endow. 15(4): 752-765 (2021) - [j57]David Alexander Tedjopurnomo, Xiucheng Li, Zhifeng Bao, Gao Cong, Farhana Murtaza Choudhury, A. Kai Qin:
Similar Trajectory Search with Spatio-Temporal Deep Representation Learning. ACM Trans. Intell. Syst. Technol. 12(6): 77:1-77:26 (2021) - [j56]Zhida Chen, Lisi Chen, Gao Cong, Christian S. Jensen:
Location- and keyword-based querying of geo-textual data: a survey. VLDB J. 30(4): 603-640 (2021) - [c131]Yile Chen, Xiucheng Li, Gao Cong, Zhifeng Bao, Cheng Long, Yiding Liu, Arun Kumar Chandran, Richard Ellison:
Robust Road Network Representation Learning: When Traffic Patterns Meet Traveling Semantics. CIKM 2021: 211-220 - [c130]Zhida Chen, Gao Cong, Walid G. Aref:
STAR: A Cache-based Distributed Warehouse System for Spatial Data Streams. SIGSPATIAL/GIS 2021: 606-615 - [c129]Zheng Wang, Cheng Long, Gao Cong:
Trajectory Simplification with Reinforcement Learning. ICDE 2021: 684-695 - [c128]Zheng Wang, Cheng Long, Gao Cong, Qianru Zhang:
Error-Bounded Online Trajectory Simplification with Multi-Agent Reinforcement Learning. KDD 2021: 1758-1768 - [c127]Peizhi Wu, Gao Cong:
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation. SIGMOD Conference 2021: 2009-2022 - [c126]Xiucheng Li, Jin Yao Chin, Yile Chen, Gao Cong:
Sinkhorn Collaborative Filtering. WWW 2021: 582-592 - [e3]Gao Cong, Maya Ramanath:
Proceedings of the CIKM 2021 Workshops co-located with 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), Gold Coast, Queensland, Australia, November 1-5, 2021. CEUR Workshop Proceedings 3052, CEUR-WS.org 2021 [contents] - [i20]Tu Gu, Kaiyu Feng, Gao Cong, Cheng Long, Zheng Wang, Sheng Wang:
The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data. CoRR abs/2103.04541 (2021) - [i19]Ziyang Wang, Wei Wei, Gao Cong, Xiao-Li Li, Xian-Ling Mao, Minghui Qiu:
Global Context Enhanced Graph Neural Networks for Session-based Recommendation. CoRR abs/2106.05081 (2021) - [i18]Peizhi Wu, Gao Cong:
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation. CoRR abs/2107.12295 (2021) - [i17]Hui Luo, Zhifeng Bao, Gao Cong, J. Shane Culpepper, Nguyen Lu Dang Khoa:
Let Trajectories Speak Out the Traffic Bottlenecks. CoRR abs/2107.12948 (2021) - [i16]Yuxing Han, Ziniu Wu, Peizhi Wu, Rong Zhu, Jingyi Yang, Liang Wei Tan, Kai Zeng, Gao Cong, Yanzhao Qin, Andreas Pfadler, Zhengping Qian, Jingren Zhou, Jiangneng Li, Bin Cui:
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation. CoRR abs/2109.05877 (2021) - 2020
- [j55]Hongyun Cai, Thanh Tung Nguyen, Yan Li, Vincent W. Zheng, Binbin Chen, Gao Cong, Xiaoli Li:
Modeling Marked Temporal Point Process Using Multi-relation Structure RNN. Cogn. Comput. 12(3): 499-512 (2020) - [j54]Yue Chen, Zhida Chen, Gao Cong, Ahmed R. Mahmood, Walid G. Aref:
SSTD: A Distributed System on Streaming Spatio-Textual Data. Proc. VLDB Endow. 13(11): 2284-2296 (2020) - [j53]Zheng Wang, Cheng Long, Gao Cong, Yiding Liu:
Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning. Proc. VLDB Endow. 13(11): 2312-2325 (2020) - [j52]Kaiyu Feng, Tao Guo, Gao Cong, Sourav S. Bhowmick, Shuai Ma:
SURGE: Continuous Detection of Bursty Regions Over a Stream of Spatial Objects. IEEE Trans. Knowl. Data Eng. 32(11): 2254-2268 (2020) - [c125]Shang Liu, Wanli Gu, Gao Cong, Fuzheng Zhang:
Structural Relationship Representation Learning with Graph Embedding for Personalized Product Search. CIKM 2020: 915-924 - [c124]Xiucheng Li, Gao Cong, Yun Cheng:
Spatial Transition Learning on Road Networks with Deep Probabilistic Models. ICDE 2020: 349-360 - [c123]Yiding Liu, Kaiqi Zhao, Gao Cong, Zhifeng Bao:
Online Anomalous Trajectory Detection with Deep Generative Sequence Modeling. ICDE 2020: 949-960 - [c122]Ziyang Wang, Wei Wei, Gao Cong, Xiao-Li Li, Xianling Mao, Minghui Qiu:
Global Context Enhanced Graph Neural Networks for Session-based Recommendation. SIGIR 2020: 169-178 - [c121]Shanshan Feng, Lucas Vinh Tran, Gao Cong, Lisi Chen, Jing Li, Fan Li:
HME: A Hyperbolic Metric Embedding Approach for Next-POI Recommendation. SIGIR 2020: 1429-1438 - [c120]Junghoon Kim, Tao Guo, Kaiyu Feng, Gao Cong, Arijit Khan, Farhana Murtaza Choudhury:
Densely Connected User Community and Location Cluster Search in Location-Based Social Networks. SIGMOD Conference 2020: 2199-2209 - [c119]Zhida Chen, Gao Cong, Walid G. Aref:
STAR: A Distributed Stream Warehouse System for Spatial Data. SIGMOD Conference 2020: 2761-2764 - [c118]Yile Chen, Cheng Long, Gao Cong, Chenliang Li:
Context-aware Deep Model for Joint Mobility and Time Prediction. WSDM 2020: 106-114 - [c117]Lucas Vinh Tran, Yi Tay, Shuai Zhang, Gao Cong, Xiaoli Li:
HyperML: A Boosting Metric Learning Approach in Hyperbolic Space for Recommender Systems. WSDM 2020: 609-617 - [i15]Zheng Wang, Cheng Long, Gao Cong, Yiding Liu:
Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning. CoRR abs/2003.02542 (2020) - [i14]Sheng Wang, Zhifeng Bao, J. Shane Culpepper, Gao Cong:
A Survey on Trajectory Data Management, Analytics, and Learning. CoRR abs/2003.11547 (2020) - [i13]Ziyang Wang, Wei Wei, Gao Cong, Xiao-Li Li, Xian-Ling Mao, Minghui Qiu, Shanshan Feng:
Exploring Global Information for Session-based Recommendation. CoRR abs/2011.10173 (2020) - [i12]Ziyang Wang, Wei Wei, Gao Cong, Xian-Ling Mao, Xiao-Li Li, Shanshan Feng:
Exploiting Repeated Behavior Pattern and Long-term Item dependency for Session-based Recommendation. CoRR abs/2012.05422 (2020)
2010 – 2019
- 2019
- [j51]Xiuzhen Zhang, Shuliang Wang, Gao Cong, Alfredo Cuzzocrea:
Social Big Data: Mining, Applications, and Beyond. Complex. 2019: 2059075:1-2059075:2 (2019) - [j50]Kaiyu Feng, Gao Cong, Christian S. Jensen, Tao Guo:
Finding Attribute-Aware Similar Region for Data Analysis. Proc. VLDB Endow. 12(11): 1414-1426 (2019) - [j49]Kaiqi Zhao, Gao Cong, Jin Yao Chin, Rong Wen:
Exploring market competition over topics in spatio-temporal document collections. VLDB J. 28(1): 123-145 (2019) - [j48]Yixiang Fang, Yun Li, Reynold Cheng, Nikos Mamoulis, Gao Cong:
Evaluating pattern matching queries for spatial databases. VLDB J. 28(5): 649-673 (2019) - [c116]Di Yao, Gao Cong, Chao Zhang, Jingping Bi:
Computing Trajectory Similarity in Linear Time: A Generic Seed-Guided Neural Metric Learning Approach. ICDE 2019: 1358-1369 - [c115]Zheng Wang, Cheng Long, Gao Cong, Ce Ju:
Effective and Efficient Sports Play Retrieval with Deep Representation Learning. KDD 2019: 499-509 - [c114]Lucas Vinh Tran, Tuan-Anh Nguyen Pham, Yi Tay, Yiding Liu, Gao Cong, Xiaoli Li:
Interact and Decide: Medley of Sub-Attention Networks for Effective Group Recommendation. SIGIR 2019: 255-264 - [c113]Xiucheng Li, Gao Cong, Aixin Sun, Yun Cheng:
Learning Travel Time Distributions with Deep Generative Model. WWW 2019: 1017-1027 - [r2]Gao Cong, Christian S. Jensen:
Spatio-Textual Data. Encyclopedia of Big Data Technologies 2019 - [i11]Ce Ju, Zheng Wang, Cheng Long, Xiaoyu Zhang, Gao Cong, Dong Eui Chang:
Interaction-aware Kalman Neural Networks for Trajectory Prediction. CoRR abs/1902.10928 (2019) - 2018
- [j47]Miao Xie, Sourav S. Bhowmick, Hao Su, Gao Cong, Wook-Shin Han:
PANDA: A System for Partial Topology-based Search on Large Networks. Proc. VLDB Endow. 11(12): 1966-1969 (2018) - [j46]Jialong Han, Aixin Sun, Gao Cong, Wayne Xin Zhao, Zongcheng Ji, Minh C. Phan:
Linking Fine-Grained Locations in User Comments. IEEE Trans. Knowl. Data Eng. 30(1): 59-72 (2018) - [j45]Sheng Wang, Zhifeng Bao, J. Shane Culpepper, Timos Sellis, Gao Cong:
Reverse k Nearest Neighbor Search over Trajectories. IEEE Trans. Knowl. Data Eng. 30(4): 757-771 (2018) - [c112]Jin Yao Chin, Kaiqi Zhao, Shafiq R. Joty, Gao Cong:
ANR: Aspect-based Neural Recommender. CIKM 2018: 147-156 - [c111]Yixiang Fang, Reynold Cheng, Gao Cong, Nikos Mamoulis, Yun Li:
On Spatial Pattern Matching. ICDE 2018: 293-304 - [c110]Xiucheng Li, Kaiqi Zhao, Gao Cong, Christian S. Jensen, Wei Wei:
Deep Representation Learning for Trajectory Similarity Computation. ICDE 2018: 617-628 - [c109]Shanshan Feng, Gao Cong, Arijit Khan, Xiucheng Li, Yong Liu, Yeow Meng Chee:
Inf2vec: Latent Representation Model for Social Influence Embedding. ICDE 2018: 941-952 - [c108]Kaiyu Feng, Tao Guo, Gao Cong, Sourav S. Bhowmick, Shuai Ma:
SURGE: Continuous Detection of Bursty Regions over a Stream of Spatial Objects. ICDE 2018: 1292-1295 - [c107]Yixiang Fang, Reynold Cheng, Jikun Wang, Lukito Budiman, Gao Cong, Nikos Mamoulis:
SpaceKey: Exploring Patterns in Spatial Databases. ICDE 2018: 1577-1580 - [c106]Jialong Han, Aixin Sun, Gao Cong, Wayne Xin Zhao, Zongcheng Ji, Minh C. Phan:
Linking Fine-Grained Locations in User Comments (Extended Abstract). ICDE 2018: 1763-1764 - [c105]Sheng Wang, Zhifeng Bao, J. Shane Culpepper, Timos Sellis, Gao Cong:
Reverse k Nearest Neighbor Search over Trajectories (Extended Abstract). ICDE 2018: 1785-1786 - [c104]Dezhong Yao, Peilin Zhao, Tuan-Anh Nguyen Pham, Gao Cong:
High-dimensional Similarity Learning via Dual-sparse Random Projection. IJCAI 2018: 3005-3011 - [c103]Ali Zonoozi, Jung-jae Kim, Xiao-Li Li, Gao Cong:
Periodic-CRN: A Convolutional Recurrent Model for Crowd Density Prediction with Recurring Periodic Patterns. IJCAI 2018: 3732-3738 - [c102]Yiding Liu, Kaiqi Zhao, Gao Cong:
Efficient Similar Region Search with Deep Metric Learning. KDD 2018: 1850-1859 - [c101]Tao Guo, Kaiyu Feng, Gao Cong, Zhifeng Bao:
Efficient Selection of Geospatial Data on Maps for Interactive and Visualized Exploration. SIGMOD Conference 2018: 567-582 - [c100]Xiangyu Ke, Arijit Khan, Gao Cong:
Finding Seeds and Relevant Tags Jointly: For Targeted Influence Maximization in Social Networks. SIGMOD Conference 2018: 1097-1111 - [c99]Tao Guo, Mingzhao Li, Peishan Li, Zhifeng Bao, Gao Cong:
POIsam: a System for Efficient Selection of Large-scale Geospatial Data on Maps. SIGMOD Conference 2018: 1677-1680 - [e2]Junhu Wang, Gao Cong, Jinjun Chen, Jianzhong Qi:
Databases Theory and Applications - 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, Proceedings. Lecture Notes in Computer Science 10837, Springer 2018, ISBN 978-3-319-92012-2 [contents] - [r1]Kaiqi Zhao, Quan Yuan, Gao Cong:
Spatiotemporal Topic Detection from Social Media. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i10]Daniel Rugeles, Zhen Hai, Gao Cong, Manoranjan Dash:
Heron Inference for Bayesian Graphical Models. CoRR abs/1802.06526 (2018) - [i9]Tran Dang Quang Vinh, Tuan-Anh Nguyen Pham, Gao Cong, Xiao-Li Li:
Attention-based Group Recommendation. CoRR abs/1804.04327 (2018) - [i8]Tran Dang Quang Vinh, Yi Tay, Shuai Zhang, Gao Cong, Xiao-Li Li:
Hyperbolic Recommender Systems. CoRR abs/1809.01703 (2018) - [i7]Zheng Wang, Ce Ju, Gao Cong, Cheng Long:
Representation Learning for Spatial Graphs. CoRR abs/1812.06668 (2018) - 2017
- [j44]Yiding Liu, Tuan-Anh Nguyen Pham, Gao Cong, Quan Yuan:
An Experimental Evaluation of Point-of-interest Recommendation in Location-based Social Networks. Proc. VLDB Endow. 10(10): 1010-1021 (2017) - [j43]Long Guo, Dongxiang Zhang, Gao Cong, Wei Wu, Kian-Lee Tan:
Influence Maximization in Trajectory Databases. IEEE Trans. Knowl. Data Eng. 29(3): 627-641 (2017) - [j42]Zhen Hai, Gao Cong, Kuiyu Chang, Peng Cheng, Chunyan Miao:
Analyzing Sentiments in One Go: A Supervised Joint Topic Modeling Approach. IEEE Trans. Knowl. Data Eng. 29(6): 1172-1185 (2017) - [j41]Xutao Li, Michael K. Ng, Gao Cong, Yunming Ye, Qingyao Wu:
MR-NTD: Manifold Regularization Nonnegative Tucker Decomposition for Tensor Data Dimension Reduction and Representation. IEEE Trans. Neural Networks Learn. Syst. 28(8): 1787-1800 (2017) - [j40]Miao Xie, Sourav S. Bhowmick, Gao Cong, Qing Wang:
PANDA: toward partial topology-based search on large networks in a single machine. VLDB J. 26(2): 203-228 (2017) - [c98]Shanshan Feng, Gao Cong, Bo An, Yeow Meng Chee:
POI2Vec: Geographical Latent Representation for Predicting Future Visitors. AAAI 2017: 102-108 - [c97]Zhuoxuan Jiang, Shanshan Feng, Gao Cong, Chunyan Miao, Xiaoming Li:
A Novel Cascade Model for Learning Latent Similarity from Heterogeneous Sequential Data of MOOC. EMNLP 2017: 2768-2773 - [c96]Long Guo, Dongxiang Zhang, Gao Cong, Wei Wu, Kian-Lee Tan:
Influence Maximization in Trajectory Databases. ICDE 2017: 27-28 - [c95]Shuai Ma, Kaiyu Feng, Jianxin Li, Haixun Wang, Gao Cong, Jinpeng Huai:
Proxies for Shortest Path and Distance Queries. ICDE 2017: 61-62 - [c94]Zhida Chen, Gao Cong, Zhenjie Zhang, Tom Z. J. Fu, Lisi Chen:
Distributed Publish/Subscribe Query Processing on the Spatio-Textual Data Stream. ICDE 2017: 1095-1106 - [c93]Guangtao Wang, Jiayu Zhou, Jingjie Ni, Tingjin Luo, Wei Long, Hai Zhen, Gao Cong, Jieping Ye:
Robust Self-Tuning Sparse Subsp