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BatchHL: Answering Distance Queries on Batch-Dynamic Networks at Scale

Summary: BatchHL is a batch-dynamic framework for distance queries on evolving graphs, pairing a compact offline distance labelling with online search. It updates labellings under batch changes, with correctness, minimality, and complexity guarantees, plus validation on 14 real networks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6397
Venue
SIGMOD
Year
2022
Pagerank
5.6858492e-05
Overall Rank
7,158 | 50.90%
DOI
10.1145/3514221.3517883

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{farhan_sigmod22,
        title = {{BatchHL: Answering Distance Queries on Batch-Dynamic Networks at Scale}},
        author = {Farhan, Muhammad and Wang, Qing and Koehler, Henning},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3517883},
        url = {https://dl.acm.org/doi/10.1145/3514221.3517883},
        year = {2022}
}

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