By Professor Wenjie Zhang

Books

Fang Y; Wang K; Lin X; Zhang W, 2022, Cohesive Subgraph Search Over Large Heterogeneous Information Networks

Fang Y; Wang K; Lin X; Zhang W, 2022, Preface

Zhang W; Zou L; Maamar Z; Chen L, 2021, Preface

Zhang W; Zou L; Maamar Z; Chen L, 2021, Preface

Qin L; Zhang W; Zhang Y; Peng Y; Kato H; Wang W; Xiao C, 2020, Preface

, 2020, Software Foundations for Data Interoperability and Large Scale Graph Data Analytics, Qin L; Zhang W; Zhang Y; Peng Y; Kato H; Wang W; Xiao C, (eds.), Springer International Publishing, http://dx.doi.org/10.1007/978-3-030-61133-0

Cheema MA; Zhang W; Chang L, 2016, Preface

, 2016, Databases Theory and Applications, Cheema MA; Zhang W; Chang L, (eds.), Springer International Publishing, http://dx.doi.org/10.1007/978-3-319-46922-5

, 2013, Web Technologies and Applications, Ishikawa Y; Li J; Wang W; Zhang R; Zhang W, (eds.), Springer Berlin Heidelberg, http://dx.doi.org/10.1007/978-3-642-37401-2

Book Chapters

Wang J; Wang M; Zhou Y; Xing Z; Liu Q; Xu X; Li B; Saydam S; Zhang W; Zhu L, 2027, 'LLM-Based HSE Compliance Assessment: Benchmark, Performance, and Advancements', in , pp. 507 - 536, http://dx.doi.org/10.1007/978-981-92-2480-7_31

Kong Y; Xu Y; Wen D; Zhang Y; Li B; Zhang W, 2027, 'Temporal Bipartite Graph Representation Learning for Behavior Anomaly Detection', in , pp. 387 - 410, http://dx.doi.org/10.1007/978-981-92-2494-4_21

Wang W; Yu J; Yang Z; Ju M; Yu S; Wu J; Liu L; Liu Y; Shepherd J; Zhang W, 2026, 'AEFA: An Ensemble Framework for Fraud Detection in the Forex Market', in , pp. 34 - 49, http://dx.doi.org/10.1007/978-981-95-3459-3_3

Tang X; Ding Y; Yang Z; Chen Y; Gu Y; Yang W; Ju M; Cao X; Liu Y; Zhang W, 2026, 'Do They Understand Them? An Updated Evaluation on Nonbinary Pronoun Handling in Large Language Models', in , pp. 204 - 219, http://dx.doi.org/10.1007/978-981-95-4969-6_16

Gong Y; Wang M; Zhang Y; Zhang W; Pang S, 2024, 'A Unified Deep Learning-Based EEG Biometric Authentication System for Cross-Session Scenarios', in Advanced Data Mining and Applications 20th International Conference, ADMA 2024, Sydney, NSW, Australia, December 3–5, 2024, Proceedings, Part IV, Springer Nature, pp. 48 - 62, http://dx.doi.org/10.1007/978-981-96-0840-9_4

Jiang A; Zhang Y; Mo H; Wang M; Zhang W, 2024, 'Learning and Mapping Academic Topic Evolution Evolving - Topics in the Australian National Disability Insurance Scheme', in Advanced Data Mining and Applications 20th International Conference, ADMA 2024, Sydney, NSW, Australia, December 3–5, 2024, Proceedings, Part I, Springer Nature, pp. 131 - 145, http://dx.doi.org/10.1007/978-981-96-0811-9_10

Chen K; Wen D; Li W; Yang Z; Zhang W, 2024, 'On Compressing Historical Cliques in Temporal Graphs', in , pp. 37 - 53, http://dx.doi.org/10.1007/978-981-97-5552-3_3

Yin H; Wang K; Zhang W; Wen D; Wang X; Zhang Y, 2024, 'Discovering Densest Subgraph over Heterogeneous Information Networks', in Bao Z; Borovica-Gajic R; Qiu R; Choudhury F; Yang Z (ed.), Databases Theory and Applications, Springer Nature, pp. 341 - 355, http://dx.doi.org/10.1007/978-3-031-47843-7_24

Xu K; Fei Z; Yu J; Kong Y; Wang X; Zhang W, 2024, 'IFGNN: An Individual Fairness Awareness Model for Missing Sensitive Information Graphs', in Bao Z; Borovica-Gajic R; Qiu R; Choudhury F; Yang Z (ed.), , SPRINGER INTERNATIONAL PUBLISHING AG, pp. 287 - 300, http://dx.doi.org/10.1007/978-3-031-47843-7_20

Tan X; Guo C; Wang X; Zhang W; Chen C, 2024, 'Maximum Fairness-Aware (k, r)-Core Identification in Large Graphs', in Bao Z; Borovica-Gajic R; Qiu R; Choudhury F; Yang Z (ed.), , SPRINGER INTERNATIONAL PUBLISHING AG, pp. 273 - 286, http://dx.doi.org/10.1007/978-3-031-47843-7_19

Hao K; Yuan L; Yang Z; Zhang W; Lin X, 2023, 'Efficient and Scalable Distributed Graph Structural Clustering at Billion Scale', in , pp. 234 - 251, http://dx.doi.org/10.1007/978-3-031-30675-4_16

Fang Y; Wang K; Lin X; Zhang W, 2022, 'Comparison Analysis', in Cohesive Subgraph Search Over Large Heterogeneous Information Networks, pp. 47 - 55, http://dx.doi.org/10.1007/978-3-030-97568-5_5

Fang Y; Wang K; Lin X; Zhang W, 2022, 'CSS on Bipartite Networks', in Cohesive Subgraph Search Over Large Heterogeneous Information Networks, pp. 11 - 26, http://dx.doi.org/10.1007/978-3-030-97568-5_3

Fang Y; Wang K; Lin X; Zhang W, 2022, 'CSS on Other General HINs', in Cohesive Subgraph Search Over Large Heterogeneous Information Networks, pp. 27 - 46, http://dx.doi.org/10.1007/978-3-030-97568-5_4

Fang Y; Wang K; Lin X; Zhang W, 2022, 'Future Work and Conclusion', in Springerbriefs in Computer Science, pp. 61 - 63, http://dx.doi.org/10.1007/978-3-030-97568-5_7

Fang Y; Wang K; Lin X; Zhang W, 2022, 'Introduction', in Cohesive Subgraph Search Over Large Heterogeneous Information Networks, pp. 1 - 5, http://dx.doi.org/10.1007/978-3-030-97568-5_1

Fang Y; Wang K; Lin X; Zhang W, 2022, 'Preliminaries', in Springerbriefs in Computer Science, pp. 7 - 9, http://dx.doi.org/10.1007/978-3-030-97568-5_2

Fang Y; Wang K; Lin X; Zhang W, 2022, 'Related Work on CSMs and Solutions', in Springerbriefs in Computer Science, pp. 57 - 60, http://dx.doi.org/10.1007/978-3-030-97568-5_6

Li S; Yang Z; Zhang X; Zhang W; Lin X, 2021, 'SQL2Cypher: Automated Data and Query Migration from RDBMS to GDBMS', in Web Information Systems Engineering – WISE 2021, pp. 510 - 517, http://dx.doi.org/10.1007/978-3-030-91560-5_39

Feng X; Zhang W; Zhao X; Zhang Y; Gao Y, 2013, 'Probabilistic k-Skyband Operator over Sliding Windows', in Web-Age Information Management, Springer Nature, pp. 190 - 202, http://dx.doi.org/10.1007/978-3-642-38562-9_20

Journal articles

Jiang W; Wang M; Mo H; Dong D; Zhang Y; Zhang W, 2026, 'TemSoGraph: Learning temporal social graphs for cyberbullying prediction', Information Sciences, 753, http://dx.doi.org/10.1016/j.ins.2026.123650

Zhu S; Yuan X; Ma B; Ni W; Zhang W, 2026, 'Beyond Spatial Privacy: Protecting Trajectories with Spatio-Temporal Differential Privacy', IEEE Transactions on Knowledge and Data Engineering, 38, pp. 5678 - 5691, http://dx.doi.org/10.1109/TKDE.2026.3690781

Yin H; Wang K; Zhang W; He Y; Zhang Y; Lin X, 2026, 'Motif Counting in Complex Networks: A Comprehensive Survey', ACM Computing Surveys, http://dx.doi.org/10.1145/3844607

Ma S; Wang H; Wen D; Zhang W; Huang W; Zhang Y, 2026, 'WOCD: A semi-supervised method for overlapping community detection using weak cliques', Knowledge Based Systems, 348, http://dx.doi.org/10.1016/j.knosys.2026.116397

Zhou M; Wang J; Zhang X; Campbell D; Wang K; Yuan L; Zhang W; Lin X, 2026, 'ProbDiffFlow: an efficient learning-free framework for probabilistic single-image optical flow estimation', Frontiers of Computer Science, 20, http://dx.doi.org/10.1007/s11704-025-50259-6

Meng L; Yuan L; Lin X; Li C; Wang K; Zhang W, 2026, 'Counting Butterflies over Streaming Bipartite Graphs with Duplicate Edges', IEEE Transactions on Knowledge and Data Engineering, 38, pp. 4200 - 4212, http://dx.doi.org/10.1109/TKDE.2026.3682749

Luo Q; Yang Z; Zhang W; Zhou A; Yu D; Cheng X; Lin X; Guo S, 2026, 'Hypergraph decomposition with intersection bounds', VLDB Journal, 35, http://dx.doi.org/10.1007/s00778-026-00985-5

Yu J; Wang H; Zhang Y; Zhang W; Qin L; Lai L; Yang B, 2026, 'MGDN: A Graph of Graphs Neural Network for Malware Detection', IEEE Transactions on Knowledge and Data Engineering, 38, pp. 4542 - 4555, http://dx.doi.org/10.1109/TKDE.2026.3689176

Yu Y; Wen D; Qin L; Cheng D; Zhang Y; Zhang W; Lin X, 2026, 'On querying minimum spanning tree in temporal graphs', VLDB Journal, 35, http://dx.doi.org/10.1007/s00778-026-00989-1

Li F; Wang X; Cheng D; Zhang Y; Zhang W; Lin X, 2026, 'Fairness-Aware Hypergraph Self-Supervised Learning With Sampling-Efficient Signals', IEEE Transactions on Knowledge and Data Engineering, 38, pp. 3611 - 3625, http://dx.doi.org/10.1109/TKDE.2026.3676748

Lu Z; Wen D; Li W; Lin X; Zhang W, 2026, 'Maintaining Biconnected Components in Streaming Graphs', Proceedings of the ACM on Management of Data, 4, pp. 1 - 25, http://dx.doi.org/10.1145/3802084

Zhang W; Yang Z; Wen D; Ding Y; Zhang W; Lin X, 2026, 'Nucleus Decomposition Revisited: An Efficient Counting-Based Approach', Proceedings of the ACM on Management of Data, 4, pp. 1 - 26, http://dx.doi.org/10.1145/3802092

Gou X; Zou L; Yu JX; Zhang W, 2026, 'An Extensive Experimental Study of Indexes in Continuous Subgraph Matching: [Experiments & Analysis]', Proceedings of the ACM on Management of Data, 4, pp. 1 - 26, http://dx.doi.org/10.1145/3786623

He Y; Zhang W; Wang K; Lin X; Zhang Y; Ni W, 2026, 'Efficient and Effective Biclique Counting with Local Differential Privacy', Proceedings of the ACM on Management of Data, 4, pp. 1 - 24, http://dx.doi.org/10.1145/3786642

Khan A; Luo Y; Zhang W; Zhou M; Zhou X, 2026, 'Retrieval-augmented Generation (RAG): What is There for Data Management Researchers? A discussion on research from a panel at LLM+Vector Data Workshop @ IEEE ICDE 2025', SIGMOD Record, 54, pp. 33 - 42, http://dx.doi.org/10.1145/3793217.3793229

Li C; Ni W; Ding M; Qu Y; Chen J; Zhang W; Rakotoarivelo T, 2026, 'C2P-M: Critical Connection Protection in Multiplex Graphs', IEEE Transactions on Knowledge and Data Engineering, 38, pp. 1512 - 1526, http://dx.doi.org/10.1109/TKDE.2026.3655741

Sun R; Chen C; Wang X; Zhang W; Zhang Y; Lin X, 2026, 'Efficient Maximal Balanced CliPlex Enumeration in Signed Graphs', IEEE Transactions on Knowledge and Data Engineering, 38, pp. 261 - 275, http://dx.doi.org/10.1109/TKDE.2025.3623162

Yang Y; Gong J; Sun H; Choo A; Mar JC; Wei Y; Zhang Y; Zhang W; Shu M; Tuong ZK; Yu D, 2026, 'Feature-preserving manifold approximation and projection to analyze single-cell data', Nature Computational Science, http://dx.doi.org/10.1038/s43588-026-00970-6

Xu L; Wen D; Qin L; Zhang W; Wang X; Lin X, 2026, 'On Querying Historical Connectivity in Large-scale Temporal Graphs', VLDB Journal, 35, http://dx.doi.org/10.1007/s00778-025-00951-7

Zhu S; Sun C; Yuan X; Li C; Ni W; Zhang W, 2026, 'Privacy Budgeting for Spatio-Temporal Trajectories', IEEE Transactions on Knowledge and Data Engineering, http://dx.doi.org/10.1109/TKDE.2026.3718033

Li F; Wang X; Cheng D; Zhang W; Chen C; Zhang Y; Lin X, 2026, 'TCGU: Data-Centric Graph Unlearning Based on Transferable Condensation', IEEE Transactions on Knowledge and Data Engineering, 38, pp. 1334 - 1348, http://dx.doi.org/10.1109/TKDE.2025.3638465

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