By Professor Wenjie Zhang

Conference Papers

Zhang W; Lin X; Cheema MA; Zhang Y; Wang W, 2010, 'Quantile-based KNN over multi-valued objects', in Proceedings International Conference on Data Engineering, pp. 16 - 27, http://dx.doi.org/10.1109/ICDE.2010.5447877

Zhang W; Zhang Y; Lin X; Cheema MA, 2010, 'Best Paper Award --- Counting Distinct Objects over Sliding Windows', in (Best Paper Award) Counting Distinct Objects over Sliding Windows, Brisbane, Australia, presented at ADC 2010, Brisbane, Australia, 18 January 2010 - 22 January 2010, http://www.itee.uq.edu.au/~adc2010

Yang S; Zhang W; Zhang Y; Lin X, 2009, 'Probabilistic Threshold Range Aggregate Query Processing over Uncertain Data (the Best Paper of the Conference)', in Proceedings of APWeb/WAIM 2009, LNCS, Springer-Verlag, Berlin, presented at APWEB / WAIM 2009, Suzhou China, 01 April 2009 - 04 April 2009

Zhang Y; Lin X; Tao Y; Zhang W, 2009, 'Uncertain Location Based Range Aggregates in a Multi-dimensional Space', in Proceedings of the 25th International Conference on Data Engineering, IEEE Computer Society, USA, presented at 25th IEEE International Conference on Data Engineering ICDE 2009, Shanghai, China, 01 April 2009

Zhang W; Lin X; Zhang Y; Wang W; Yu JX, 2009, 'Probabilistic Skyline Operator over Sliding Windows', in Proceedings of the 25th International Conference on Data Engineering, IEEE Computer Society, USA, presented at International Conference on Data Engineering, Shanghai China, 29 March 2009 - 02 April 2009, http://dx.doi.org/10.1109/ICDE.2009.83

Zhang W; Lin X; Pei J; Zhang Y, 2008, 'Managing uncertain data: Probabilistic approaches', in 9th International Conference on Web-Age Information Management, WAIM 2008, Zhangjia jie, China, presented at 9th International Conference on Web-Age Information Management, WAIM 2008, Zhangjia jie, China, 20 July 2008 - 22 July 2008

Hua M; Pei J; Zhang W; Lin X, 2008, 'Ranking queries on uncertain data: a probabilistic threshold approach', in 2008 ACM SIGMOD international conference, Vancouver BC Canada, presented at ACM SIGMOD international conference on management of data, 2008, Vancouver BC Canada, 09 June 2008 - 12 June 2008

Hua M; Pei J; Zhang W; Lin X, 2008, 'Efficiently answering probabilistic threshold top-k queries on uncertain data', in 24th international conference on data engineering, Mexico, presented at IEEE 24th International Conference on Data Engineering, ICDE`08 2008, Mexico, 07 April 2008 - 12 April 2008

Conference Proceedings (Editor of)

Zhang W; Tung A; Zheng Z; Yang Z; Wang X; Guo H, (eds.), 2024, 'Web and Big Data - 8th International Joint Conference, APWeb-WAIM 2024, Jinhua, China, August 30 - September 1, 2024, Proceedings, Part I', presented at APWeb-WAIM 2024, 30 August 2024, http://dx.doi.org/10.1007/978-981-97-7232-2

Zhang W; Tung A; Zheng Z; Yang Z; Wang X; Guo H, (eds.), 2024, 'Web and Big Data - 8th International Joint Conference, APWeb-WAIM 2024, Jinhua, China, August 30 - September 1, 2024, Proceedings, Part II', presented at APWeb-WAIM 2024, 30 August 2024, http://dx.doi.org/10.1007/978-981-97-7235-3

Zhang W; Tung A; Zheng Z; Yang Z; Wang X; Guo H, (eds.), 2024, 'Web and Big Data - 8th International Joint Conference, APWeb-WAIM 2024, Jinhua, China, August 30 - September 1, 2024, Proceedings, Part III', presented at APWeb-WAIM 2024, 30 August 2024, http://dx.doi.org/10.1007/978-981-97-7238-4

Zhang W; Tung A; Zheng Z; Yang Z; Wang X; Guo H, (eds.), 2024, 'Web and Big Data - 8th International Joint Conference, APWeb-WAIM 2024, Jinhua, China, August 30 - September 1, 2024, Proceedings, Part IV', presented at APWeb-WAIM 2024, 30 August 2024, http://dx.doi.org/10.1007/978-981-97-7241-4

Zhang W; Tung A; Zheng Z; Yang Z; Wang X; Guo H, (eds.), 2024, 'Web and Big Data - 8th International Joint Conference, APWeb-WAIM 2024, Jinhua, China, August 30 - September 1, 2024, Proceedings, Part V', presented at APWeb-WAIM 2024, 30 August 2024, http://dx.doi.org/10.1007/978-981-97-7244-5

Conference Abstracts

Wang X; Wen D; Qin L; Chang L; Zhang W, 2022, 'ScaleG: A Distributed Disk-based System for Vertex-centric Graph Processing (Extended Abstract)', in Proceedings International Conference on Data Engineering, Vol. 2022-May, pp. 1511 - 1512, http://dx.doi.org/10.1109/ICDE53745.2022.00132

Preprints

Zhai Z; Qing S; Wang X; Zhang W, 2025, SGPT: Few-Shot Prompt Tuning for Signed Graphs, http://dx.doi.org/10.48550/arxiv.2412.12155

Xie T; Wan Y; Liu Y; Zeng Y; Wang S; Zhang W; Grazian C; Kit C; Ouyang W; Zhou D; Hoex B, 2025, DARWIN 1.5: Large Language Models as Materials Science Adapted Learners, http://dx.doi.org/10.48550/arxiv.2412.11970

Ye Y; Ren J; Wang S; Wan Y; Razzak I; Hoex B; Wang H; Xie T; Zhang W, 2025, Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model, http://dx.doi.org/10.48550/arxiv.2404.03080

Yu J; Wang H; Chen C; Wang X; Qin L; Zhang W; Zhang Y; Liu X, 2025, RIDA: A Robust Attack Framework on Incomplete Graphs, http://dx.doi.org/10.48550/arxiv.2407.18170

He Y; Wang K; Zhang W; Lin X; Zhang Y, 2025, Common Neighborhood Estimation over Bipartite Graphs under Local Differential Privacy, http://dx.doi.org/10.48550/arxiv.2502.01904

Sima Q; Yu J; Wang X; Zhang W; Zhang Y; Lin X, 2025, Deep Overlapping Community Search via Subspace Embedding, http://dx.doi.org/10.48550/arxiv.2404.14692

Xie T; Zhang H; Wang S; Wan Y; Razzak I; Kit C; Zhang W; Hoex B, 2024, ByteScience: Bridging Unstructured Scientific Literature and Structured Data with Auto Fine-tuned Large Language Model in Token Granularity, http://dx.doi.org/10.48550/arxiv.2411.12000

Wan Y; Xie T; Wu N; Zhang W; Kit C; Hoex B, 2024, From Tokens to Materials: Leveraging Language Models for Scientific Discovery, http://dx.doi.org/10.48550/arxiv.2410.16165

Wan Y; Liu Y; Ajith A; Grazian C; Hoex B; Zhang W; Kit C; Xie T; Foster I, 2024, SciQAG: A Framework for Auto-Generated Science Question Answering Dataset with Fine-grained Evaluation, http://dx.doi.org/10.48550/arxiv.2405.09939

Li C; Ni W; Ding M; Qu Y; Chen J; Smith D; Zhang W; Rakotoarivelo T, 2024, Decentralized Privacy Preservation for Critical Connections in Graphs, http://dx.doi.org/10.48550/arxiv.2405.11713

Yuan L; Hao K; Lin X; Zhang W, 2024, Batch Hop-Constrained s-t Simple Path Query Processing in Large Graphs, http://dx.doi.org/10.48550/arxiv.2312.01424

Xie T; Wan Y; Huang W; Yin Z; Liu Y; Wang S; Linghu Q; Kit C; Grazian C; Zhang W; Razzak I; Hoex B, 2023, DARWIN Series: Domain Specific Large Language Models for Natural Science, http://dx.doi.org/10.48550/arxiv.2308.13565

Jin J; Cheng P; Chen L; Lin X; Zhang W, 2023, Efficient Non-Learning Similar Subtrajectory Search, http://dx.doi.org/10.48550/arxiv.2307.10082

Luo L; Fang Y; Lu M; Cao X; Zhang X; Zhang W, 2023, GSim: A Graph Neural Network based Relevance Measure for Heterogeneous Graphs, http://dx.doi.org/10.48550/arxiv.2208.06144

Xie T; Wan Y; Huang W; Zhou Y; Liu Y; Linghu Q; Wang S; Kit C; Grazian C; Zhang W; Hoex B, 2023, Large Language Models as Master Key: Unlocking the Secrets of Materials Science with GPT, http://dx.doi.org/10.48550/arxiv.2304.02213

Yang Z; Zhang W; Lin X; Zhang Y; Li S, 2023, HGMatch: A Match-by-Hyperedge Approach for Subgraph Matching on Hypergraphs, http://dx.doi.org/10.48550/arxiv.2302.06119

Sun Q; Zhang W; Lin X, 2022, Progressive Hard Negative Masking: From Global Uniformity to Local Tolerance, http://dx.doi.org/10.36227/techrxiv.21203096

Chen Z; Yuan L; Lin X; Qin L; Zhang W, 2022, Balanced Clique Computation in Signed Networks: Concepts and Algorithms, http://dx.doi.org/10.48550/arxiv.2204.00515

Linghu Q; Zhang F; Lin X; Zhang W; Zhang Y, 2021, Towards User Engagement Dynamics in Social Networks, http://dx.doi.org/10.48550/arxiv.2110.12193

Luo L; Fang Y; Cao X; Zhang X; Zhang W, 2021, Detecting Communities from Heterogeneous Graphs: A Context Path-based Graph Neural Network Model, http://dx.doi.org/10.48550/arxiv.2109.02058

Yang Z; Lai L; Lin X; Hao K; Zhang W, 2021, HUGE: An Efficient and Scalable Subgraph Enumeration System, http://dx.doi.org/10.48550/arxiv.2103.14294

Chen X; Huang C; Yao L; Wang X; Liu W; Zhang W, 2020, Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation, http://dx.doi.org/10.48550/arxiv.2004.08068

Lai L; Qing Z; Yang Z; Jin X; Lai Z; Wang R; Hao K; Lin X; Qin L; Zhang W; Zhang Y; Qian Z; Zhou J, 2019, A Survey and Experimental Analysis of Distributed Subgraph Matching, http://dx.doi.org/10.48550/arxiv.1906.11518

Wang Y; Lin X; Wu L; Zhang W, 2017, Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval, http://dx.doi.org/10.48550/arxiv.1701.05003

Shao Q; Yuan L; Lin X; Zhang W, Augmenting the Intelligence of Large Language Model-Based Agents with Graphs: A Survey, http://dx.doi.org/10.20944/preprints202609.0138.v1

Ukey N; Zhang G; Yang Z; Li B; Li W; Zhang W, Efficient Continuous kNN Join over Dynamic High-dimensional Data [v1], http://dx.doi.org/10.21203/rs.3.rs-2572561/v1

Ukey N; Zhang G; Yang Z; Li B; Li W; Zhang W, Efficient Continuous kNN Join over Dynamic High-dimensional Data [v2], http://dx.doi.org/10.21203/rs.3.rs-2572561/v2

Ukey N; Zhang G; Yang Z; Li B; Li W; Zhang W, Efficient Continuous kNN Join over Dynamic High-dimensional Data [v3], http://dx.doi.org/10.21203/rs.3.rs-2572561/v3

Ukey N; Zhang G; Yang Z; Li B; Li W; Zhang W, Efficient Continuous kNN Join over Dynamic High-dimensional Data [v4], http://dx.doi.org/10.21203/rs.3.rs-2572561/v4

Su G; Wang H; Zhang Y; Coster AC; Wilkins MR; Canete PF; Yu D; Yang Y; Zhang W, Inferring gene regulatory networks by hypergraph variational autoencoder, http://dx.doi.org/10.1101/2024.04.01.586509

Xie T; Wan Y; Liu Y; Zeng Y; Wang S; Zhang W; Grazian C; Kit C; Ouyang W; Zhou D; Hoex B, Large Language Models as Materials Science Adapted Learners, http://dx.doi.org/10.21203/rs.3.rs-6752901/v1

Sun Q; Zhang W; Lin X, Progressive Hard Negative Masking: From Global Uniformity to Local Tolerance, http://dx.doi.org/10.36227/techrxiv.21203096.v1

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