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Toward a Distance Oracle for Billion-Node Graphs

Summary: Proposes scalable distance oracles for graphs with billions of nodes using sketch-based encodings. Optimizes landmark selection, distributed BFS, and answer generation to balance space, speed, and accuracy; validated on real and synthetic networks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11126
Venue
VLDB
Year
2014
Pagerank
5.6719349e-05
Overall Rank
7,211 | 50.53%
DOI
10.14778/2732219.2732225

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{qi_vldb14,
        title = {{Toward a Distance Oracle for Billion-Node Graphs}},
        author = {Qi, Zichao and Xiao, Yanghua and Shao, Bin and Wang, Haixun},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {2},
        pages = {61--72},
        doi = {10.14778/2732219.2732225},
        url = {https://doi.org/10.14778/2732219.2732225},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

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

Rank Cited Paper Year Venue Pagerank
3 Pregel: A System for Large-Scale Graph Processing 2010 SIGMOD 0.0012250108
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