Zhongying Zhao

Orcid: 0000-0002-5880-0225

Affiliations:

Shandong University of Science and Technology (SDUST), College of Computer Science and Engineering, Qingdao, China
Chinese Academy of Sciences (CAS), Shenzhen Institutes of Advanced Technology, Beijing, China (2012-2014)
Chinese Academy of Sciences (CAS), Institute of Computing Technology, Beijing, China (PhD 2012)

According to our database¹, Zhongying Zhao authored at least 84 papers between 2007 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2026

Efficiently Harmonizing Information Sharing for Heterogeneous Graph Contrastive Learning.

[BibT_eX]

[DOI]

Pattern Recognit., 2026

Reconsidering the interplay between behaviors: A cross-attentive behavior-aware GCN-based recommendation.

[BibT_eX]

[DOI]

Pattern Recognit., 2026

2025

Boosting Performance of Graph Convolutional Networks via Generating Pseudolabels and Feature Interaction.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Soc. Syst., August, 2025

Boosting graph contrastive learning via adaptive graph augmentation and topology-feature-level homophily.

[BibT_eX]

[DOI]

Int. J. Mach. Learn. Cybern., August, 2025

Dual-Channel Multiplex Graph Neural Networks for Recommendation.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., June, 2025

Lightweight yet Efficient: An External Attentive Graph Convolutional Network with Positional Prompts for Sequential Recommendation.

[BibT_eX]

[DOI]

Jinyu Zhang

Chao Li

Zhongying Zhao

ACM Trans. Inf. Syst., May, 2025

Self-supervised progressive graph neural network for enhanced multi-behavior recommendation.

[BibT_eX]

[DOI]

Int. J. Mach. Learn. Cybern., March, 2025

Towards user-specific multimodal recommendation via cross-modal attention-enhanced graph convolution network.

[BibT_eX]

[DOI]

Ruidong Wang

Chao Li

Zhongying Zhao

Appl. Intell., January, 2025

Local High-order Structure-aware Graph Neural Network for motif prediction.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2025

GraphBSSN: A simple yet effective generative method for node classification in class-imbalanced graphs.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2025

NodeHGAE: Node-oriented heterogeneous graph autoencoder.

[BibT_eX]

[DOI]

Inf. Sci., 2025

Fusion3M: Community-based multi-scale co-evolving network for dynamic graph representation learning.

[BibT_eX]

[DOI]

Inf. Fusion, 2025

Encoder augmentation for multi-task graph contrastive learning.

[BibT_eX]

[DOI]

Neurocomputing, 2025

Span-level emotion-cause-category triplet extraction via table-filling.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2025

Improving the quality of Positive and Negative Samples based on Topological Analysis and Counterfactual Reasoning for Graph Contrastive Learning.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2025

LeDA-GNN: Learnable dual augmentation for graph neural networks.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2025

Popularity-aware dynamic graph neural collaborative filtering with local-global convergence.

[BibT_eX]

[DOI]

Xiaoxue Yang

Hui Zhou

Zhongying Zhao

Appl. Soft Comput., 2025

Span-level emotion-cause-category triplet extraction with instruction tuning LLMs and data augmentation.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2025

CoLA-Former: Graph Transformer Using Communal Linear Attention for Lightweight Sequential Recommendation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Generate or Re-Weight? A Mutual-Guidance Method for Class-Imbalanced Graphs.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

MaskDGNN: Self-Supervised Dynamic Graph Neural Networks with Activeness-aware Temporal Masking.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

UMGAD: Unsupervised Multiplex Graph Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

Lightweight Yet Fine-Grained: A Graph Capsule Convolutional Network with Subspace Alignment for Shared-Account Sequential Recommendation.

[BibT_eX]

[DOI]

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

A Fast and Robust Attention-Free Heterogeneous Graph Convolutional Network.

[BibT_eX]

[DOI]

IEEE Trans. Big Data, October, 2024

DGNN-MN: Dynamic Graph Neural Network via memory regenerate and neighbor propagation.

[BibT_eX]

[DOI]

Appl. Intell., October, 2024

MHGNN: Multi-view fusion based Heterogeneous Graph Neural Network.

[BibT_eX]

[DOI]

Appl. Intell., September, 2024

MHGCN+: Multiplex Heterogeneous Graph Convolutional Network.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., June, 2024

Higher order heterogeneous graph neural network based on node attribute enhancement.

[BibT_eX]

[DOI]

Expert Syst. Appl., March, 2024

Heterogeneous graph knowledge distillation neural network incorporating multiple relations and cross-semantic interactions.

[BibT_eX]

[DOI]

Inf. Sci., February, 2024

Multi-Channel Hypergraph Contrastive Learning for Matrix Completion.

[BibT_eX]

[DOI]

CoRR, 2024

Dual-Channel Multiplex Graph Neural Networks for Recommendation.

[BibT_eX]

[DOI]

CoRR, 2024

2023

BA-GNN: Behavior-aware graph neural network for session-based recommendation.

[BibT_eX]

[DOI]

Frontiers Comput. Sci., December, 2023

Self-Paced Co-Training of Graph Neural Networks for Semi-Supervised Node Classification.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., November, 2023

Adversarial variational autoencoder for attributed graph embedding with high-frequency noise filtering.

[BibT_eX]

[DOI]

Appl. Intell., November, 2023

HetGNN-SF: Self-supervised learning on heterogeneous graph neural network via semantic strength and feature similarity.

[BibT_eX]

[DOI]

Appl. Intell., October, 2023

Dual Feature Interaction-Based Graph Convolutional Network.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., September, 2023

Self-supervised contrastive learning on heterogeneous graphs with mutual constraints of structure and feature.

[BibT_eX]

[DOI]

Inf. Sci., September, 2023

OSGNN: Original graph and Subgraph aggregated Graph Neural Network.

[BibT_eX]

[DOI]

Expert Syst. Appl., September, 2023

Session-based recommendation with hypergraph convolutional networks and sequential information embeddings.

[BibT_eX]

[DOI]

Expert Syst. Appl., August, 2023

HGNN-ETA: Heterogeneous graph neural network enriched with text attribute.

[BibT_eX]

[DOI]

World Wide Web (WWW), July, 2023

AF-GCN: Attribute-Fusing Graph Convolution Network for Recommendation.

[BibT_eX]

[DOI]

IEEE Trans. Big Data, April, 2023

SMGCL: Semi-supervised Multi-view Graph Contrastive Learning.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2023

HetReGAT-FC: Heterogeneous Residual Graph Attention Network via Feature Completion.

[BibT_eX]

[DOI]

Inf. Sci., 2023

Community detection based on unsupervised attributed network embedding.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2023

2022

Heterogeneous graph neural network for attribute completion.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2022

Deep cognitive diagnosis model for predicting students' performance.

[BibT_eX]

[DOI]

Future Gener. Comput. Syst., 2022

Latent semantic-enhanced discrete hashing for cross-modal retrieval.

[BibT_eX]

[DOI]

Appl. Intell., 2022

Multiplex Heterogeneous Graph Convolutional Network.

[BibT_eX]

[DOI]

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

GuessUNeed: Recommending Courses via Neural Attention Network and Course Prerequisite Relation Embeddings.

[BibT_eX]

[DOI]

ACM Trans. Multim. Comput. Commun. Appl., 2021

Inductive Representation Learning via CNN for Partially-Unseen Attributed Networks.

[BibT_eX]

[DOI]

IEEE Trans. Netw. Sci. Eng., 2021

Learning emotional word embeddings for sentiment analysis.

[BibT_eX]

[DOI]

J. Intell. Fuzzy Syst., 2021

Sentiment classification based on dependency-relationship embedding and attention mechanism.

[BibT_eX]

[DOI]

J. Intell. Fuzzy Syst., 2021

HEPre: Click frequency prediction of applications based on heterogeneous information network embedding.

[BibT_eX]

[DOI]

J. Intell. Fuzzy Syst., 2021

DeepEmLAN: Deep embedding learning for attributed networks.

[BibT_eX]

[DOI]

Inf. Sci., 2021

Network Embedding Based Collaborative Filtering Model Equipped With User Purchase Motivation and Potential Interactions.

[BibT_eX]

[DOI]

Proceedings of the 7th IEEE International Conference on Cloud Computing and Intelligent Systems, 2021

2020

HetNERec: Heterogeneous network embedding based recommendation.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2020

A comparative study on heterogeneous information network embeddings.

[BibT_eX]

[DOI]

J. Intell. Fuzzy Syst., 2020

2019

Digital image self-recovery algorithm based on improved joint source-channel coding optimizer.

[BibT_eX]

[DOI]

Multim. Tools Appl., 2019

An incremental method to detect communities in dynamic evolving social networks.

[BibT_eX]

[DOI]

Enrique Herrera-Viedma

Knowl. Based Syst., 2019

Identifying High Influential Users in Social Media by Analyzing Users' Behaviors.

[BibT_eX]

[DOI]

J. Intell. Fuzzy Syst., 2019

Rank2vec: Learning node embeddings with local structure and global ranking.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2019

Attention-Based Deep Learning Model for Predicting Collaborations Between Different Research Affiliations.

[BibT_eX]

[DOI]

IEEE Access, 2019

An Interpretable and Scalable Recommendation Method Based on Network Embedding.

[BibT_eX]

[DOI]

IEEE Access, 2019

Logic Petri Net Synthesis for Cooperative Systems.

[BibT_eX]

[DOI]

IEEE Access, 2019

Learner2Vec-Based Learner Community Evolution Analysis-A Case Study Involving Student Card Data.

[BibT_eX]

[DOI]

IEEE Access, 2019

Modeling the Effort and Learning Ability of Students in MOOCs.

[BibT_eX]

[DOI]

IEEE Access, 2019

2018

A comparative study on community detection methods in complex networks.

[BibT_eX]

[DOI]

J. Intell. Fuzzy Syst., 2018

Identifying advisor-advisee relationships from co-author networks via a novel deep model.

[BibT_eX]

[DOI]

Inf. Sci., 2018

2017

Efficiently detecting overlapping communities using seeding and semi-supervised learning.

[BibT_eX]

[DOI]

Int. J. Mach. Learn. Cybern., 2017

A system to manage and mine microblogging data.

[BibT_eX]

[DOI]

J. Intell. Fuzzy Syst., 2017

2016

Probability model selection and parameter evolutionary estimation for clustering imbalanced data without sampling.

[BibT_eX]

[DOI]

Neurocomputing, 2016

Realtime Channel Recommendation: Switch Smartly While Watching TV.

[BibT_eX]

[DOI]

Proceedings of the Frontiers in Algorithmics, 10th International Workshop, 2016

2015

Identifying and Analyzing Popular Phrases Multi-Dimensionally in Social Media Data.

[BibT_eX]

[DOI]

Int. J. Data Warehous. Min., 2015

Collecting, managing and analyzing social networking data effectively.

[BibT_eX]

[DOI]

Proceedings of the 12th International Conference on Fuzzy Systems and Knowledge Discovery, 2015

2014

Efficient Detecting Overlapping Communities by Seeding and Semi-Supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2014

Detecting and Analyzing Influenza Epidemics with Social Media in China.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2014

A Spatial-Temporal Analysis of Users' Geographical Patterns in Social Media: A Case Study on Microblogs.

[BibT_eX]

[DOI]

Proceedings of the Database Systems for Advanced Applications, 2014

2012

Topic oriented community detection through social objects and link analysis in social networks.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2012

Relationships between geographical cluster and cyberspace community: A case study on microblog.

[BibT_eX]

[DOI]

Proceedings of the 20th International Conference on Geoinformatics, 2012

2011

Info-Cluster Based Regional Influence Analysis in Social Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2011

2010

Personalized Knowledge Acquisition through Interactive Data Analysis in E-learning System.

[BibT_eX]

[DOI]

J. Comput., 2010

2009

Course ontology-based user's knowledge requirement acquisition from behaviors within e-learning systems.

[BibT_eX]

[DOI]

Qingtian Zeng

Zhongying Zhao

Yongquan Liang

Comput. Educ., 2009

2007

Mining User's Interest from Reading Behavior in E-learning System.

[BibT_eX]

[DOI]

Yongquan Liang

Zhongying Zhao

Qingtian Zeng

Proceedings of the 8th ACIS International Conference on Software Engineering, 2007

A New Clustering Algorithm Based on Token Ring.

[BibT_eX]

[DOI]

Yongquan Liang

Jiancong Fan

Zhongying Zhao

Proceedings of the 8th ACIS International Conference on Software Engineering, 2007

Zhongying Zhao

Timeline

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