Mining triadic closure patterns in social networks. - Hong Huang 001; Jie Tang 001; Sen Wu 001; Lu Liu 005; Xiaoming Fu 001 (WWW (Companion Volume), 2014)

Triadic Closure Pattern Analysis and Prediction in Social Networks. - Hong Huang 001; Jie Tang 001; Lu Liu 005; Jarder Luo; Xiaoming Fu 001 (IEEE Trans. Knowl. Data Eng., 2015)

Predicting Happiness State Based on Emotion Representative Mining in Online Social Networks. - Xiao Zhang 015; Wenzhong Li; Hong Huang 001; Cam-Tu Nguyen; Xu Chen 004; Xiaoliang Wang 001; Sanglu Lu (PAKDD (1), 2017)

MomentSA: A Fast and Accurate Method for Stochastic Kronecker Graph Parameter Computing. - Yongqiang Li; Zhiyuan Shao; Hong Huang 001; Yinuo Li; Hai Jin 001 (CSCWD, 2018)

Identifying Topical Opinion Leaders in Social Community Question Answering. - Tao Zhao 007; Hong Huang 001; Xiaoming Fu 001 (DASFAA (1), 2018)

A comparative analysis of school pupils' daily habits in Germany and China. - Xiaoming Fu 001; Hong Huang 001; Xiang-Yang Li 001; Haisheng Tan; Jie Tang 001 (INFOCOM Workshops, 2018)

GRAM: A GPU-Based Property Graph Traversal and Query for HPC Rich Metadata Management. - Wenke Li; Xuanhua Shi; Hong Huang 001; Peng Zhao; Hai Jin 001; Dong Dai 001; Yong Chen 001 (NPC, 2018)

A Preliminary Study of E-Commerce User Behavior Based on Mobile Big Data - Invited Paper. - Bo Zhao 010; Hong Huang 001; Jarder Luo; Xinggang Wang; Xiaoming Yao; Ramin Yahyapour; Zhenxuan Wang; Xiaoming Fu 001 (VTC Spring, 2018)

A Cross-Platform Consumer Behavior Analysis of Large-Scale Mobile Shopping Data. - Hong Huang 001; Bo Zhao 010; Hao Zhao; Zhou Zhuang; Zhenxuan Wang; Xiaoming Yao; Xinggang Wang; Hai Jin 001; Xiaoming Fu 001 (WWW, 2018)

DeepScan: Exploiting Deep Learning for Malicious Account Detection in Location-Based Social Networks. - Qingyuan Gong; Yang Chen 001; Xinlei He 001; Zhou Zhuang; Tianyi Wang 001; Hong Huang 001; Xin Wang 002; Xiaoming Fu 001 (IEEE Commun. Mag., 2018)

Will Triadic Closure Strengthen Ties in Social Networks? - Hong Huang 001; Yuxiao Dong; Jie Tang 001; Hongxia Yang; Nitesh V. Chawla; Xiaoming Fu 001 (ACM Trans. Knowl. Discov. Data, 2018)

Decoding Homomorphically Encrypted Flac Audio without Decryption. - Yuanyuan Tang; Bin Zhu 008; Xiaojing Ma 002; P. Takis Mathiopoulos; Xia Xie; Hong Huang 001 (ICASSP, 2019)

Estimating Socioeconomic Status via Temporal-Spatial Mobility Analysis - A Case Study of Smart Card Data. - Shichang Ding; Hong Huang 001; Tao Zhao 007; Xiaoming Fu 001 (ICCCN, 2019)

Dependent task placement and scheduling with function configuration in edge computing. - Liuyan Liu; Haisheng Tan; Shaofeng H.-C. Jiang; Zhenhua Han; Xiang-Yang Li 001; Hong Huang 001 (IWQoS, 2019)

High Performance DDoS Attack Detection System Based on Distribution Statistics. - Xia Xie; Jinpeng Li; Xiaoyang Hu; Hai Jin 001; Hanhua Chen; Xiaojing Ma 002; Hong Huang 001 (NPC, 2019)

TPLP: Two-Phase Selection Link Prediction for Vertex in Graph Streams. - Yang Xiao; Hong Huang 001; Feng Zhao 003; Hai Jin 001 (PAKDD (2), 2019)

Deep Learning-based Short Video Recommendation and Prefetching for Mobile Commuting Users. - Qian Li; Yuan Zhang 013; Hong Huang 001; Jinyao Yan (NEAT@SIGCOMM, 2019)

Modeling Heterogeneous Edges to Represent Networks with Graph Auto-Encoder. - Lu Wang 002; Yu Song 005; Hong Huang 001; Fanghua Ye 001; Xuanhua Shi; Hai Jin 001 (DASFAA (2), 2020)

Maxson: Reduce Duplicate Parsing Overhead on Raw Data. - Xuanhua Shi; Yipeng Zhang; Hong Huang 001; Zhenyu Hu; Hai Jin 001; Huan Shen; Yongluan Zhou; Bingsheng He; Ruibo Li; Keyong Zhou (ICDE, 2020)

Motif-Preserving Temporal Network Embedding. - Hong Huang 001; Zixuan Fang; Xiao Wang 017; Youshan Miao; Hai Jin 001 (IJCAI, 2020)

Information Diffusion Prediction with Personalized Graph Neural Networks. - Yao Wu; Hong Huang 001; Hai Jin 001 (KSEM (2), 2020)

Outlier Resilient Collaborative Web Service QoS Prediction. - Fanghua Ye 001; Zhiwei Lin; Chuan Chen 001; Zibin Zheng; Hong Huang 001; Emine Yilmaz (CoRR, 2020)

Predicting individual socioeconomic status from mobile phone data: a semi-supervised hypergraph-based factor graph approach. - Tao Zhao 007; Hong Huang 001; Xiaoming Yao; Jarder Luo; Xiaoming Fu 001 (Int. J. Data Sci. Anal., 2020)

Semantic and Syntactic Enhanced Aspect Sentiment Triplet Extraction. - Zhexue Chen; Hong Huang 001; Bang Liu; Xuanhua Shi; Hai Jin 001 (ACL/IJCNLP (Findings), 2021)

Temporal Heterogeneous Information Network Embedding. - Hong Huang 001; Ruize Shi; Wei Zhou; Xiao Wang 017; Hai Jin 001; Xiaoming Fu 001 (IJCAI, 2021)

Outlier-Resilient Web Service QoS Prediction. - Fanghua Ye 001; Zhiwei Lin; Chuan Chen 001; Zibin Zheng; Hong Huang 001 (WWW, 2021)

Multi-Task Representation Learning with Multi-View Graph Convolutional Networks. - Hong Huang 001; Yu Song 005; Yao Wu; Jia Shi; Xia Xie; Hai Jin 001 (CoRR, 2021)

China in the eyes of news media: a case study under COVID-19 epidemic. - Hong Huang 001; Zhexue Chen; Xuanhua Shi; Chenxu Wang; Zepeng He; Hai Jin 001; Mingxin Zhang; Zongya Li (Frontiers Inf. Technol. Electron. Eng., 2021)

Enhancing Graph Neural Networks via auxiliary training for semi-supervised node classification. - Yao Wu; Yu Song 005; Hong Huang 001; Fanghua Ye 001; Xing Xie 001; Hai Jin 001 (Knowl. Based Syst., 2021)

Mining World Indicators for Analyzing and Modeling the Development of Countries. - Hong Huang 001; Mingyuan Chi; Yu Song 005; Hai Jin 001 (Trans. Data Sci., 2021)

Multi-Stage Network Embedding for Exploring Heterogeneous Edges. - Hong Huang 001; Yu Song 005; Fanghua Ye 001; Xing Xie 001; Xuanhua Shi; Hai Jin 001 (ACM Trans. Knowl. Discov. Data, 2021)

Core decomposition and maintenance in weighted graph. - Wei Zhou; Hong Huang 001; Qiang-Sheng Hua; Dongxiao Yu; Hai Jin 001; Xiaoming Fu 001 (World Wide Web, 2021)

Friend Recommendations with Self-Rescaling Graph Neural Networks. - Xiran Song; Jianxun Lian; Hong Huang 001; Mingqi Wu; Hai Jin 001; Xing Xie 001 (KDD, 2022)

Enhance Temporal Knowledge Graph Completion via Time-Aware Attention Graph Convolutional Network. - HaoHui Wei; Hong Huang 001; Teng Zhang 001; Xuanhua Shi; Hai Jin 001 (ECML/PKDD (2), 2022)

Ada-GNN: Adapting to Local Patterns for Improving Graph Neural Networks. - Zihan Luo 001; Jianxun Lian; Hong Huang 001; Hai Jin 001; Xing Xie 001 (WSDM, 2022)

Show Me the Whole World: Towards Entire Item Space Exploration for Interactive Personalized Recommendations. - Yu Song 005; Shuai Sun; Jianxun Lian; Hong Huang 001; Yu Li; Hai Jin 001; Xing Xie 001 (WSDM, 2022)

Multitask Representation Learning With Multiview Graph Convolutional Networks. - Hong Huang 001; Yu Song 005; Yao Wu; Jia Shi; Xia Xie; Hai Jin 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

Modeling Information Diffusion With Sequential Interactive Hypergraphs. - Hai Jin 001; Yao Wu; Hong Huang 001; Yu Song 005; HaoHui Wei; Xuanhua Shi (IEEE Trans. Sustain. Comput., 2022)

Cross-links Matter for Link Prediction: Rethinking the Debiased GNN from a Data Perspective. - Zihan Luo 001; Hong Huang 001; Jianxun Lian; Xiran Song; Xing Xie 001; Hai Jin 001 (NeurIPS, 2023)

xGCN: An Extreme Graph Convolutional Network for Large-scale Social Link Prediction. - Xiran Song; Jianxun Lian; Hong Huang 001; Zihan Luo 001; Wei Zhou; Xue Lin 005; Mingqi Wu; Chaozhuo Li; Xing Xie 001; Hai Jin 001 (WWW, 2023)

Revisiting Core Maintenance for Dynamic Hypergraphs. - Qiang-Sheng Hua; Xiaohui Zhang 016; Hai Jin 001; Hong Huang 001 (IEEE Trans. Parallel Distributed Syst., 2023)

Temporal Heterogeneous Information Network Embedding via Semantic Evolution. - Wei Zhou; Hong Huang 001; Ruize Shi; Xiran Song; Xue Lin 005; Xiao Wang 017; Hai Jin 001 (IEEE Trans. Knowl. Data Eng., 2023)

An Efficient Subgraph-Inferring Framework for Large-Scale Heterogeneous Graphs. - Wei Zhou; Hong Huang 001; Ruize Shi; Kehan Yin; Hai Jin 001 (AAAI, 2024)

CausalNET: Unveiling Causal Structures on Event Sequences by Topology-Informed Causal Attention. - Hua Zhu; Hong Huang 001; Kehan Yin; Zejun Fan; Hai Jin 001; Bang Liu (IJCAI, 2024)

Orthogonality Matters: Invariant Time Series Representation for Out-of-distribution Classification. - Ruize Shi; Hong Huang 001; Kehan Yin; Wei Zhou; Hai Jin 001 (KDD, 2024)

Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections. - Zihan Luo 001; Hong Huang 001; Yongkang Zhou; Jiping Zhang; Nuo Chen; Hai Jin 001 (NeurIPS, 2024)

GraphInstruct: Empowering Large Language Models with Graph Understanding and Reasoning Capability. - Zihan Luo 001; Xiran Song; Hong Huang 001; Jianxun Lian; Chenhao Zhang 005; Jinqi Jiang; Xing Xie 001 (CoRR, 2024)

OCDB: Revisiting Causal Discovery with a Comprehensive Benchmark and Evaluation Framework. - Wei Zhou; Hong Huang 001; Guowen Zhang; Ruize Shi; Kehan Yin; Yuanyuan Lin; Bang Liu (CoRR, 2024)

From General to Specific: Tailoring Large Language Models for Personalized Healthcare. - Ruize Shi; Hong Huang 001; Wei Zhou; Kehan Yin; Kai Zhao; Yun Zhao (CoRR, 2024)

Media Power Measuring via Emotional Contagion. - Xue Lin 005; Hong Huang 001; Zongya Li; Hai Jin 001 (J. Soc. Comput., 2024)

XGCN: a library for large-scale graph neural network recommendations. - Xiran Song; Hong Huang 001; Jianxun Lian; Hai Jin 001 (Frontiers Comput. Sci., 2024)

Towards Controllable Hybrid Fairness in Graph Neural Networks. - Zihan Luo 001; Hong Huang 001; Jianxun Lian; Xiran Song; Hai Jin 001 (KDD (1), 2025)

Soft-GNN: towards robust graph neural networks via self-adaptive data utilization. - Yao Wu; Hong Huang 001; Yu Song 005; Hai Jin 001 (Frontiers Comput. Sci., 2025)

Efficient Learning for Billion-Scale Heterogeneous Information Networks. - Ruize Shi; Hong Huang 001; Xue Lin 005; Kehan Yin; Wei Zhou; Hai Jin 001 (IEEE Trans. Big Data, 2025)