Select Publications

Books

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

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

Book Chapters

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, Springer International Publishing, 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 Berlin Heidelberg, pp. 190 - 202, http://dx.doi.org/10.1007/978-3-642-38562-9_20

Journal articles

Huang C; Fang Y; Lin X; Cao X; Zhang W, 2022, 'ABLE: Meta-Path Prediction in Heterogeneous Information Networks', ACM Transactions on Knowledge Discovery from Data, vol. 16, pp. 1 - 21, http://dx.doi.org/10.1145/3494558

Hidayat A; Cheema MA; Lin X; Zhang W; Zhang Y, 2022, 'Continuous monitoring of moving skyline and top-k queries', VLDB Journal, vol. 31, pp. 459 - 482, http://dx.doi.org/10.1007/s00778-021-00702-4

Zhang X; Wang H; Yu J; Chen C; Wang X; Zhang W, 2022, 'Polarity-based graph neural network for sign prediction in signed bipartite graphs', World Wide Web, vol. 25, pp. 471 - 487, http://dx.doi.org/10.1007/s11280-022-01015-4

Chang L; Feng X; Yao K; Qin L; Zhang W, 2022, 'Accelerating Graph Similarity Search via Efficient GED Computation', IEEE Transactions on Knowledge and Data Engineering, http://dx.doi.org/10.1109/TKDE.2022.3153523

Peng Y; Lin X; Zhang Y; Zhang W; Qin L, 2022, 'Answering reachability and K-reach queries on large graphs with label constraints', VLDB Journal, vol. 31, pp. 101 - 127, http://dx.doi.org/10.1007/s00778-021-00695-0

Zhang X; Wang H; Yu J; Chen C; Wang X; Zhang W, 2022, 'Bipartite graph capsule network', World Wide Web, http://dx.doi.org/10.1007/s11280-022-01009-2

Xu Y; Yin Y; Wang J; Wei J; Liu J; Yao L; Zhang W, 2021, 'Unsupervised Cross-View Feature Selection on incomplete data[Formula presented]', Knowledge-Based Systems, vol. 234, http://dx.doi.org/10.1016/j.knosys.2021.107595

Li C; Zhang F; Zhang Y; Qin L; Zhang W; Lin X, 2021, 'Discovering fortress-like cohesive subgraphs', Knowledge and Information Systems, vol. 63, pp. 3217 - 3250, http://dx.doi.org/10.1007/s10115-021-01624-x

Ma C; Fang Y; Cheng R; Lakshmanan LVS; Zhang W; Lin X, 2021, 'On Directed Densest Subgraph Discovery', ACM Transactions on Database Systems, vol. 46, http://dx.doi.org/10.1145/3483940

Luo L; Fang Y; Cao X; Zhang X; Zhang W, 2021, 'CP-GNN: A Software for Community Detection in Heterogeneous Information Networks[Formula presented]', Software Impacts, vol. 10, http://dx.doi.org/10.1016/j.simpa.2021.100169

Peng Y; Lin X; Zhang Y; Zhang W; Qin L; Zhou J, 2021, 'Efficient Hop-constrained s-t Simple Path Enumeration', VLDB Journal, vol. 30, pp. 799 - 823, http://dx.doi.org/10.1007/s00778-021-00674-5

He Y; Wang K; Zhang W; Lin X; Zhang Y, 2021, 'Exploring cohesive subgraphs with vertex engagement and tie strength in bipartite graphs', Information Sciences, vol. 572, pp. 277 - 296, http://dx.doi.org/10.1016/j.ins.2021.04.027

Yang J; Yao W; Zhang W, 2021, 'Keyword Search on Large Graphs: A Survey', Data Science and Engineering, vol. 6, pp. 142 - 162, http://dx.doi.org/10.1007/s41019-021-00154-4

Zhang H; Huang Z; Lin X; Lin Z; Zhang W; Zhang Y, 2021, 'Efficient and High-Quality Seeded Graph Matching: Employing Higher-order Structural Information', ACM Transactions on Knowledge Discovery from Data, vol. 15, http://dx.doi.org/10.1145/3442340

Ma C; Fang Y; Cheng R; Lakshmanan LVS; Zhang W; Lin X, 2021, 'Efficient Directed Densest Subgraph Discovery', SIGMOD Record, vol. 50, pp. 33 - 40, http://dx.doi.org/10.1145/3471485.3471494

Huang Z; Lin X; Zhang W; Zhang Y, 2021, 'Communication-efficient distributed covariance sketch, with application to distributed PCA', Journal of Machine Learning Research, vol. 22

Wang K; Zhang W; Zhang Y; Qin L; Zhang Y, 2021, 'Discovering Significant Communities on Bipartite Graphs: An Index-based Approach', IEEE Transactions on Knowledge and Data Engineering, http://dx.doi.org/10.1109/TKDE.2021.3111349

Hao K; Yuan L; Zhang W, 2021, 'Distributed Hop-Constrained s-t Simple Path Enumeration at Billion Scale', Proceedings of the VLDB Endowment, vol. 15, pp. 169 - 182, http://dx.doi.org/10.14778/3489496.3489499

Yang Y; Fang Y; Orlowska ME; Zhang W; Lin X, 2021, 'Efficient bi-triangle counting for large bipartite networks', Proceedings of the VLDB Endowment, vol. 14, pp. 984 - 996, http://dx.doi.org/10.14778/3447689.3447702

Lin Z; Zhang F; Lin X; Zhang W; Tian Z, 2021, 'Hierarchical core maintenance on large dynamic graphs', Proceedings of the VLDB Endowment, vol. 14, pp. 757 - 770, http://dx.doi.org/10.14778/3446095.3446099

Wang X; Wen D; Qin L; Chang L; Zhang Y; Zhang W, 2021, 'ScaleG: A Distributed Disk-based System for Vertex-centric Graph Processing', IEEE Transactions on Knowledge and Data Engineering, pp. 1 - 1, http://dx.doi.org/10.1109/TKDE.2021.3101057

Wen D; Yang B; Zhang Y; Qin L; Cheng D; Zhang W, 2021, 'Span-reachability querying in large temporal graphs', VLDB Journal, http://dx.doi.org/10.1007/s00778-021-00715-z

Fang Y; Huang X; Qin L; Zhang Y; Zhang W; Cheng R; Lin X, 2020, 'Correction: A survey of community search over big graphs (The VLDB Journal, (2020), 29, 1, (353-392), 10.1007/s00778-019-00556-x)', VLDB Journal, vol. 29, pp. 1219, http://dx.doi.org/10.1007/s00778-019-00592-7

Liu B; Yuan L; Lin X; Qin L; Zhang W; Zhou J, 2020, 'Efficient (α , β)-core computation in bipartite graphs', VLDB Journal, vol. 29, pp. 1075 - 1099, http://dx.doi.org/10.1007/s00778-020-00606-9

Li W; Zhang Y; Sun Y; Wang W; Li M; Zhang W; Lin X, 2020, 'Approximate Nearest Neighbor Search on High Dimensional Data - Experiments, Analyses, and Improvement', IEEE Transactions on Knowledge and Data Engineering, vol. 32, pp. 1475 - 1488, http://dx.doi.org/10.1109/TKDE.2019.2909204

Chen H; Fang Y; Zhang Y; Zhang W; Wang L, 2020, 'ESPM: Efficient Spatial Pattern Matching', IEEE Transactions on Knowledge and Data Engineering, vol. 32, pp. 1227 - 1233, http://dx.doi.org/10.1109/TKDE.2019.2947505

Zhang F; Li C; Zhang Y; Qin L; Zhang W, 2020, 'Finding Critical Users in Social Communities: The Collapsed Core and Truss Problems', IEEE Transactions on Knowledge and Data Engineering, vol. 32, pp. 78 - 91, http://dx.doi.org/10.1109/TKDE.2018.2880976

Zhang F; Lin X; Zhang Y; Qin L; Zhang W, 2019, 'Efficient community discovery with user engagement and similarity', VLDB Journal, vol. 28, pp. 987 - 1012, http://dx.doi.org/10.1007/s00778-019-00579-4

Yang J; Zhang Y; Zhang W; Lin X, 2019, 'Cost optimization based on influence and user preference', Knowledge and Information Systems, vol. 61, pp. 695 - 732, http://dx.doi.org/10.1007/s10115-018-1290-y

Yang Y; Zhang W; Zhang Y; Lin X; Wang L, 2019, 'Selectivity Estimation on Set Containment Search', Data Science and Engineering, vol. 4, pp. 254 - 268, http://dx.doi.org/10.1007/s41019-019-00104-1

Li Y; Fang Y; Cheng R; Zhang W, 2019, 'Spatial pattern matching', SIGSPATIAL Special, vol. 11, pp. 3 - 12, http://dx.doi.org/10.1145/3355491.3355493

Yu W; Lin X; Zhang W; Pei J; McCann JA, 2019, 'SimRank*: effective and scalable pairwise similarity search based on graph topology', VLDB Journal, vol. 28, pp. 401 - 426, http://dx.doi.org/10.1007/s00778-018-0536-3

Liu W; Shen X; Du B; Tsang IW; Zhang W; Lin X, 2019, 'Hyperspectral imagery classification via stochastic HHSVMs', IEEE Transactions on Image Processing, vol. 28, pp. 577 - 588, http://dx.doi.org/10.1109/TIP.2018.2869691

Wang K; Lin X; Qin L; Zhang W; Zhang Y, 2019, 'Vertex priority based butterfly counting for large-scale bipartite networks', Proceedings of the VLDB Endowment, vol. 12, pp. 1139 - 1152, http://dx.doi.org/10.14778/3339490.3339497

Feng X; Chang L; Lin X; Qin L; Zhang W; Yuan L, 2018, 'Distributed computing connected components with linear communication cost', Distributed and Parallel Databases, vol. 36, pp. 555 - 592, http://dx.doi.org/10.1007/s10619-018-7232-6

Yang J; Zhang W; Yang S; Zhang Y; Lin X; Yuan L, 2018, 'Efficient set containment join', VLDB Journal, vol. 27, pp. 471 - 495, http://dx.doi.org/10.1007/s00778-018-0505-x

Yuan L; Qin L; Zhang W; Chang L; Yang J, 2018, 'Index-Based Densest Clique Percolation Community Search in Networks', IEEE Transactions on Knowledge and Data Engineering, vol. 30, pp. 922 - 935, http://dx.doi.org/10.1109/TKDE.2017.2783933

Yu W; Lin X; Zhang W; McCann JA, 2018, 'Dynamical SimRank search on time-varying networks', VLDB Journal, vol. 27, pp. 79 - 104, http://dx.doi.org/10.1007/s00778-017-0488-z

Zhao X; Xiao C; Lin X; Zhang W; Wang Y, 2018, 'Efficient structure similarity searches: a partition-based approach', VLDB Journal, vol. 27, pp. 53 - 78, http://dx.doi.org/10.1007/s00778-017-0487-0

Liu W; Xu D; Tsang I; Zhang W, 2018, 'Metric Learning for Multi-output Tasks', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, pp. 408 - 422, http://dx.doi.org/10.1109/TPAMI.2018.2794976

Wang X; Zhang W; Yan J; Yuan X; Zha H, 2018, 'On the flexibility of block coordinate descent for large-scale optimization', Neurocomputing, vol. 272, pp. 471 - 480, http://dx.doi.org/10.1016/j.neucom.2017.07.024

Wang X; Zhang W; Zhang Y; Lin X; Huang Z, 2017, 'Top-k spatial-keyword publish/subscribe over sliding window', VLDB Journal, vol. 26, pp. 301 - 326, http://dx.doi.org/10.1007/s00778-016-0453-2

Yuan L; Qin L; Lin X; Chang L; Zhang W, 2017, 'I/O efficient ECC graph decomposition via graph reduction', VLDB Journal, vol. 26, pp. 275 - 300, http://dx.doi.org/10.1007/s00778-016-0451-4

Yang S; Cheema MA; Lin X; Zhang Y; Zhang W, 2017, 'Reverse k nearest neighbors queries and spatial reverse top-k queries', VLDB Journal, vol. 26, pp. 151 - 176, http://dx.doi.org/10.1007/s00778-016-0445-2

Yang J; Zhang W; Zhang Y; Wang X; Lin X, 2017, 'Categorical top-k spatial influence query', World Wide Web, vol. 20, pp. 175 - 203, http://dx.doi.org/10.1007/s11280-016-0383-3

Wang Y; Lin X; Wu L; Zhang W, 2017, 'Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval', IEEE Transactions on Image Processing, vol. 26, pp. 1393 - 1404, http://dx.doi.org/10.1109/TIP.2017.2655449


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