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2024, 'An Empirical Analysis of Just-in-Time Compilation in Modern Databases', in Lecture Notes in Computer Science, Springer Nature Switzerland, pp. 227 - 240, http://dx.doi.org/10.1007/978-3-031-47843-7_16
,2024, 'kNN Join for Dynamic High-Dimensional Data: A Parallel Approach', in Lecture Notes in Computer Science, Springer Nature Switzerland, pp. 3 - 16, http://dx.doi.org/10.1007/978-3-031-47843-7_1
,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
,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
,2024, 'Towards efficient simulation-based constrained temporal graph pattern matching', World Wide Web, 27, http://dx.doi.org/10.1007/s11280-024-01259-2
,2024, 'Application of Semi-Supervised Learning in Image Classification: Research on Fusion of Labeled and Unlabeled Data', IEEE Access, 12, pp. 27331 - 27343, http://dx.doi.org/10.1109/ACCESS.2024.3367772
,2024, 'Prototype Comparison Convolutional Networks for One-Shot Segmentation', IEEE Access, 12, pp. 54978 - 54990, http://dx.doi.org/10.1109/ACCESS.2024.3387742
,2023, 'Efficient continuous kNN join over dynamic high-dimensional data', World Wide Web, 26, pp. 3759 - 3794, http://dx.doi.org/10.1007/s11280-023-01204-9
,2023, 'Machine Learning Methods in Weather and Climate Applications: A Survey', Applied Sciences (Switzerland), 13, http://dx.doi.org/10.3390/app132112019
,2023, 'Survey on Exact kNN Queries over High-Dimensional Data Space', Sensors, 23, http://dx.doi.org/10.3390/s23020629
,2022, 'Deep Learning-Based Image Recognition of Agricultural Pests', Applied Sciences (Switzerland), 12, http://dx.doi.org/10.3390/app122412896
,2021, 'FAST: FPGA-based Subgraph Matching on Massive Graphs', arXiv preprint arXiv:2102.10768
,2019, 'A Survey and Experimental Analysis of Distributed Subgraph Matching', arXiv preprint arXiv:1906.11518
,2024, 'Efficient Exact and Approximate Betweenness Centrality Computation for Temporal Graphs', in WWW 2024 - Proceedings of the ACM Web Conference, pp. 2395 - 2406, http://dx.doi.org/10.1145/3589334.3645438
,2024, 'TATKC: A Temporal Graph Neural Network for Fast Approximate Temporal Katz Centrality Ranking', in WWW 2024 - Proceedings of the ACM Web Conference, pp. 527 - 538, http://dx.doi.org/10.1145/3589334.3645432
,2023, 'Efficient Distributed Core Graph Decomposition', in IEEE International Conference on Data Mining Workshops, ICDMW, pp. 1023 - 1031, http://dx.doi.org/10.1109/ICDMW60847.2023.00135
,2023, 'HGMatch: A Match-by-Hyperedge Approach for Subgraph Matching on Hypergraphs', in Proceedings - International Conference on Data Engineering, pp. 2063 - 2076, http://dx.doi.org/10.1109/ICDE55515.2023.00160
,2022, 'Efficient kNN Join over Dynamic High-Dimensional Data', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 63 - 75, http://dx.doi.org/10.1007/978-3-031-15512-3_5
,2022, 'Hop-Constrained s-t Simple Path Enumeration in Billion-Scale Labelled Graphs', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 49 - 64, http://dx.doi.org/10.1007/978-3-031-20891-1_5
,2022, 'Hop-Constrained s-t Simple Path Enumeration in Large Uncertain Graphs', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 115 - 127, http://dx.doi.org/10.1007/978-3-031-15512-3_9
,2021, 'HUGE: An Efficient and Scalable Subgraph Enumeration System', in Proceedings of the ACM SIGMOD International Conference on Management of Data, Virtual Event China, pp. 2049 - 2062, presented at SIGMOD/PODS '21: International Conference on Management of Data, Virtual Event China, 20 June 2021, http://dx.doi.org/10.1145/3448016.3457237
,2020, 'An empirical study on recent graph database systems', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 328 - 340, http://dx.doi.org/10.1007/978-3-030-55130-8_29
,2019, 'PatMat: A distributed pattern matching engine with Cypher', in International Conference on Information and Knowledge Management, Proceedings, pp. 2921 - 2924, http://dx.doi.org/10.1145/3357384.3357840
,2019, 'Improving distribued subgraph matching algorithm on timely dataflow', in Proceedings - 2019 IEEE 35th International Conference on Data Engineering Workshops, ICDEW 2019, pp. 266 - 273, http://dx.doi.org/10.1109/ICDEW.2019.000-2
,2019, 'Distributed Subgraph Matching on Timely Dataflow', in Proc. VLDB Endow., VLDB Endowment, pp. 1099–1112 - 1099–1112, http://dx.doi.org/10.14778/3339490.3339494
,2023, An Empirical Analysis of Just-in-Time Compilation in Modern Databases, , http://dx.doi.org/10.1007/978-3-031-47843-7_16
,2023, Machine Learning Methods in Weather and Climate Applications: A Survey, , http://dx.doi.org/10.20944/preprints202309.1764.v2
,2023, Machine Learning Methods in Climate Prediction: A Survey, , http://dx.doi.org/10.20944/preprints202309.1764.v1
,2023, HGMatch: A Match-by-Hyperedge Approach for Subgraph Matching on Hypergraphs, , http://arxiv.org/abs/2302.06119v2
,2023, Structure of the Native Chemotaxis Core Signalling Unit from E-gene lysedE. colicells, , http://dx.doi.org/10.1101/2023.01.30.526190
,2021, HUGE: An Efficient and Scalable Subgraph Enumeration System, , http://dx.doi.org/10.48550/arxiv.2103.14294
,2021, FAST: FPGA-based Subgraph Matching on Massive Graphs, , http://dx.doi.org/10.48550/arxiv.2102.10768
,2019, A Survey and Experimental Analysis of Distributed Subgraph Matching, , http://dx.doi.org/10.48550/arxiv.1906.11518
,Efficient Continuous kNN Join over Dynamic High-dimensional Data [v1], , http://dx.doi.org/10.21203/rs.3.rs-2572561/v1
,Efficient Continuous kNN Join over Dynamic High-dimensional Data [v2], , http://dx.doi.org/10.21203/rs.3.rs-2572561/v2
,Efficient Continuous kNN Join over Dynamic High-dimensional Data [v3], , http://dx.doi.org/10.21203/rs.3.rs-2572561/v3
,Efficient Continuous kNN Join over Dynamic High-dimensional Data [v4], , http://dx.doi.org/10.21203/rs.3.rs-2572561/v4
,Towards Efficient Simulation-Based Constrained Temporal Graph Pattern Matching, , http://dx.doi.org/10.2139/ssrn.4187676
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