Haobing Liu

39 papers A* 4A 6Journal 24Unranked 5
YearRankTypeTitle / Venue / Authors
2026 A conf
Adaptive Continual Learning with User-Incremental Forward Compatibility for Meta-Augmented Cold-Start Recommenders.
WSDM
Chunyang Wang, Xuhao Zhao, Wenze Ma, Zhaobo Wang, Yanmin Zhu, Haobing Liu
2026 J jnl
Optimizing resource allocation for wind turbine maintenance through process and fault data fusion.
Inf. Fusion
Huiling Li, Cong Liu, Qinjun Du, Qingtian Zeng, Haobing Liu, Qingle Wang, Long Cheng
2026 A* conf
ScaleGNN: Towards Scalable Graph Neural Networks via Adaptive High-order Neighboring Feature Fusion.
WWW
Xiang Li, Jianpeng Qi, Haobing Liu, Yuan Cao, Guoqing Chao, Zhongying Zhao, Junyu Dong, Xinwang Liu, Yanwei Yu
2026 A* conf
Weighted Graph Clustering via Scale Contraction and Graph Structure Learning.
WWW
Haobing Liu, Yinuo Zhang, Tingting Wang, Ruobing Jiang, Yanwei Yu
2026 J jnl
Weighted Graph Clustering via Scale Contraction and Graph Structure Learning.
CoRR
Haobing Liu, Yinuo Zhang, Tingting Wang, Ruobing Jiang, Yanwei Yu
2025 A conf
Exploring the Tradeoff Between Diversity and Discrimination for Continuous Category Discovery.
CIKM
Ruobing Jiang, Yang Liu, Haobing Liu, Yanwei Yu, Chunyang Wang
2025 J jnl
Exploring the Tradeoff Between Diversity and Discrimination for Continuous Category Discovery.
CoRR
Ruobing Jiang, Yang Liu, Haobing Liu, Yanwei Yu, Chunyang Wang
2025 J jnl
Geometry-Aware Protein-Protein Binding Site Prediction Using Geometric Learning and Pretraining Strategies.
J. Chem. Inf. Model.
Wenhong Xu, Yuqian Xie, Huasen Jiang, Yu Fu, Haobing Liu, Zhiqiang Wei, Shugang Zhang
2025 A conf
Hierarchy-Consistent Learning and Adaptive Loss Balancing for Hierarchical Multi-Label Classification.
CIKM
Ruobing Jiang, Mengzhe Liu, Haobing Liu, Yanwei Yu
2025 J jnl
Hierarchy-Consistent Learning and Adaptive Loss Balancing for Hierarchical Multi-Label Classification.
CoRR
Ruobing Jiang, Mengzhe Liu, Haobing Liu, Yanwei Yu
2025 J jnl
Incorporating Attributes and Multi-Scale Structures for Heterogeneous Graph Contrastive Learning.
CoRR
Ruobing Jiang, Yacong Li, Haobing Liu, Yanwei Yu
2025 J jnl
Incorporating attributes and multi-scale structures for heterogeneous graph contrastive learning.
Inf. Fusion
Ruobing Jiang, Yacong Li, Haobing Liu, Yanwei Yu
2025 A* conf
MaskDGNN: Self-Supervised Dynamic Graph Neural Networks with Activeness-aware Temporal Masking.
IJCAI
Yiming He, Xiang Li, Zhongying Zhao, Haobing Liu, Peilan He, Yanwei Yu
2025 J jnl
ScaleGNN: Towards Scalable Graph Neural Networks via Adaptive High-order Neighboring Feature Fusion.
CoRR
Xiang Li, Haobing Liu, Jianpeng Qi, Yuan Cao, Guoqing Chao, Yanwei Yu
2025 J jnl
Weighted Graph Structure Learning with Attention Denoising for Node Classification.
CoRR
Tingting Wang, Jiaxin Su, Haobing Liu, Ruobing Jiang
2024 — conf
Incorporating Higher-order Structural Information for Graph Clustering.
DASFAA (4)
Qiankun Li, Haobing Liu, Ruobing Jiang, Tingting Wang
2024 J jnl
Incorporating Higher-order Structural Information for Graph Clustering.
CoRR
Qiankun Li, Haobing Liu, Ruobing Jiang, Tingting Wang
2023 J jnl
A Survey on Cross-domain Recommendation: Taxonomies, Methods, and Future Directions.
ACM Trans. Inf. Syst.
Tianzi Zang, Yanmin Zhu, Haobing Liu, Ruohan Zhang, Jiadi Yu
2023 J jnl
Incorporating Heterogeneous User Behaviors and Social Influences for Predictive Analysis.
IEEE Trans. Big Data
Haobing Liu, Yanmin Zhu, Chunyang Wang, Jianyu Ding, Jiadi Yu, Feilong Tang
2023 J jnl
Learning Aspect-Aware High-Order Representations from Ratings and Reviews for Recommendation.
ACM Trans. Knowl. Discov. Data
Ke Wang, Yanmin Zhu, Haobing Liu, Tianzi Zang, Chunyang Wang
2023 J jnl
Learning Shared Representations for Recommendation with Dynamic Heterogeneous Graph Convolutional Networks.
ACM Trans. Knowl. Discov. Data
Mengyuan Jing, Yanmin Zhu, Yanan Xu, Haobing Liu, Tianzi Zang, Chunyang Wang, Jiadi Yu
2023 J jnl
Modeling Multi-aspect Preferences and Intents for Multi-behavioral Sequential Recommendation.
CoRR
Haobing Liu, Jianyu Ding, Yanmin Zhu, Feilong Tang, Jiadi Yu, Ruobing Jiang, Zhongwen Guo
2023 J jnl
Modeling multi-aspect preferences and intents for multi-behavioral sequential recommendation.
Knowl. Based Syst.
Haobing Liu, Jianyu Ding, Yanmin Zhu, Feilong Tang, Jiadi Yu, Ruobing Jiang, Zhongwen Guo
2023 J jnl
Multifaceted Relation-aware Meta-learning with Dual Customization for User Cold-start Recommendation.
ACM Trans. Knowl. Discov. Data
Chunyang Wang, Yanmin Zhu, Haobing Liu, Tianzi Zang, Ke Wang, Jiadi Yu
2022 J jnl
Deep Meta-learning in Recommendation Systems: A Survey.
CoRR
Chunyang Wang, Yanmin Zhu, Haobing Liu, Tianzi Zang, Jiadi Yu, Feilong Tang
2022 J jnl
Graph-Enhanced Spatial-Temporal Network for Next POI Recommendation.
ACM Trans. Knowl. Discov. Data
Zhaobo Wang, Yanmin Zhu, Qiaomei Zhang, Haobing Liu, Chunyang Wang, Tong Liu
2022 J jnl
Incorporating Heterogeneous User Behaviors and Social Influences for Predictive Analysis.
CoRR
Haobing Liu, Yanmin Zhu, Chunyang Wang, Jianyu Ding, Jiadi Yu, Feilong Tang
2022 — conf
Inter- and Intra-Domain Relation-Aware Heterogeneous Graph Convolutional Networks for Cross-Domain Recommendation.
DASFAA (2)
Ke Wang, Yanmin Zhu, Haobing Liu, Tianzi Zang, Chunyang Wang, Kuan Liu
2022 J jnl
Jointly Modeling Heterogeneous Student Behaviors and Interactions among Multiple Prediction Tasks.
ACM Trans. Knowl. Discov. Data
Haobing Liu, Yanmin Zhu, Tianzi Zang, Yanan Xu, Jiadi Yu, Feilong Tang
2022 A* conf
Learning Graph-based Disentangled Representations for Next POI Recommendation.
SIGIR
Zhaobo Wang, Yanmin Zhu, Haobing Liu, Chunyang Wang
2022 J jnl
MPAN: Multi-parallel attention network for session-based recommendation.
Neurocomputing
Tianzi Zang, Yanmin Zhu, Jing Zhu, Yanan Xu, Haobing Liu
2021 J jnl
A Survey on Cross-domain Recommendation: Taxonomies, Methods, and Future Directions.
CoRR
Tianzi Zang, Yanmin Zhu, Haobing Liu, Ruohan Zhang, Jiadi Yu
2021 — conf
Efficient Feature Interactions Learning with Gated Attention Transformer.
WISE (2)
Chao Long, Yanmin Zhu, Haobing Liu, Jiadi Yu
2021 A conf
Enhancing User Interest Modeling with Knowledge-Enriched Itemsets for Sequential Recommendation.
CIKM
Chunyang Wang, Yanmin Zhu, Haobing Liu, Wenze Ma, Tianzi Zang, Jiadi Yu
2021 J jnl
Jointly Modeling Heterogeneous Student Behaviors and Interactions Among Multiple Prediction Tasks.
CoRR
Haobing Liu, Yanmin Zhu, Tianzi Zang, Yanan Xu, Jiadi Yu, Feilong Tang
2021 — conf
Modeling Dynamic Social Behaviors with Time-Evolving Graphs for User Behavior Predictions.
DASFAA (1)
Tianzi Zang, Yanmin Zhu, Chen Gong, Haobing Liu, Bo Li
2021 A conf
Modeling Inter-station Relationships with Attentive Temporal Graph Convolutional Network for Air Quality Prediction.
WSDM
Chunyang Wang, Yanmin Zhu, Tianzi Zang, Haobing Liu, Jiadi Yu
2020 A conf
Jointly Modeling Individual Student Behaviors and Social Influence for Prediction Tasks.
CIKM
Haobing Liu, Yanmin Zhu, Tianzi Zang, Jiadi Yu, Haibin Cai
2020 — conf
Learning from Heterogeneous Student Behaviors for Multiple Prediction Tasks.
DASFAA (2)
Haobing Liu, Yanmin Zhu, Yanan Xu