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  • Sun G, Zhao Y and Li Y. FABLE: Approximate Butterfly Counting in Bipartite Graph Stream with Duplicate Edges. Proceedings of the 33rd ACM International Conference on Information and Knowledge Management. (2158-2167).

    https://doi.org/10.1145/3627673.3679812

  • Yu C, Liu H, Wahab F, Ling Z, Ren T, Ma H and Zhao Y. (2023). Global triangle estimation based on first edge sampling in large graph streams. The Journal of Supercomputing. 79:13. (14079-14116). Online publication date: 1-Sep-2023.

    https://doi.org/10.1007/s11227-023-05205-3

  • Gou X and Zou L. (2023). Sliding window-based approximate triangle counting with bounded memory usage. The VLDB Journal — The International Journal on Very Large Data Bases. 32:5. (1087-1110). Online publication date: 1-Sep-2023.

    https://doi.org/10.1007/s00778-023-00783-3

  • Zhang F, Gou X and Zou L. (2023). Top-k heavy weight triangles listing on graph stream. World Wide Web. 26:4. (1827-1851). Online publication date: 1-Jul-2023.

    https://doi.org/10.1007/s11280-022-01117-z

  • Xue R, Wang Y, Liu S, Li Y, Tian W and Zheng W. SPAC: Scalable Pattern Approximate Counting in Graph Mining. Algorithms and Architectures for Parallel Processing. (214-232).

    https://doi.org/10.1007/978-3-031-22677-9_12

  • Yang X, Song C, Yu M, Gu J and Liu M. (2022). Distributed Triangle Approximately Counting Algorithms in Simple Graph Stream. ACM Transactions on Knowledge Discovery from Data. 16:4. (1-43). Online publication date: 31-Aug-2022.

    https://doi.org/10.1145/3494562

  • Gou X and Zou L. Sliding Window-based Approximate Triangle Counting over Streaming Graphs with Duplicate Edges. Proceedings of the 2021 International Conference on Management of Data. (645-657).

    https://doi.org/10.1145/3448016.3452800

  • Lee D, Shin K and Faloutsos C. (2020). Temporal locality-aware sampling for accurate triangle counting in real graph streams. The VLDB Journal — The International Journal on Very Large Data Bases. 29:6. (1501-1525). Online publication date: 1-Nov-2020.

    https://doi.org/10.1007/s00778-020-00624-7