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MCR-Tree: An Efficient Index for Multi-dimensional Core Search

Summary: MCR-Tree: a generic, update-aware index for multi-dimensional core search across core models ((\u03b1,\u03b2)-core, (k,l)-core, k-core). Key idea: project vertices via skyline corenesses into R-tree space, augment nodes with connectivity, enabling branch-and-bound search with far less redundancy and strong scalability. (summarized by gpt-5.4-mini on May 24 2026)

Paper ID
6979
Venue
SIGMOD
Year
2024
Pagerank
5.3849387e-05
Overall Rank
8,687 | 40.40%
DOI
10.1145/3654956

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{luo_sigmod24,
        title = {{MCR-Tree: An Efficient Index for Multi-dimensional Core Search}},
        author = {Luo, Chengyang and Zhu, Yifan and Liu, Qing and Gao, Yunjun and Chen, Lu and Xu, Jianliang},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3654956},
        url = {https://dl.acm.org/doi/10.1145/3654956},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,308 Zero-Redundancy Search for Bi-Components in Bipartite Graphs 2026 SIGMOD 5.093636e-05
10,349 Budgeted Strong Community Search in Heterogeneous Graphs 2026 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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