Scaling Up Distance Labeling on Graphs with Core-Periphery Properties
Summary: Core-Tree (CT) Index scales exact 2-hop distance labeling to massive graphs by exploiting core–periphery structure; links treewidth, index size, and query time. CT delivers a compact index with sub-0.4 ms queries on graphs as large as 5.5B edges, enabling distance queries previously infeasible. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Wentao Li
- 2. Miao Qiao
- 3. Lu Qin
- 4. Ying Zhang
- 5. Lijun Chang
- 6. Xuemin Lin
Incoming Citations (Sorted by Pagerank)
Showing 15 of 15 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 260 | Fast Exact Shortest-Path Distance Queries on Large Networks by Pruned Landmark Labeling | 2013 | SIGMOD | 0.00030040036 |
| 376 | TEDI: Efficient Shortest Path Query Answering on Graphs | 2010 | SIGMOD | 0.00025097452 |
| 1,821 | Computing Personalized PageRank Quickly by Exploiting Graph Structures | 2014 | VLDB | 0.00010423565 |
| 1,823 | Hop Doubling Label Indexing for Point-to-Point Distance Querying on Scale-Free Networks | 2014 | VLDB | 0.00010413508 |
| 2,201 | When Hierarchy Meets 2-Hop-Labeling: Efficient Shortest Distance Queries on Road Networks | 2018 | SIGMOD | 9.3048105e-05 |
| 2,639 | Scaling Distance Labeling on Small-World Networks | 2019 | SIGMOD | 8.3975113e-05 |
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