Database Paper Browser

Back to papers

Succinct Graph Representations as Distance Oracles: An Experimental Evaluation

Summary: Empirically compares 12 exact distance oracles from embeddings and other succinct representations across graphs. Embeddings offer fast setup and structured-graph accuracy; unstructured graphs degrade; GOSH-based approximations scale to 100M+ nodes. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12723
Venue
VLDB
Year
2022
Pagerank
4.1945683e-05
Overall Rank
11,376 | 20.86%
DOI
10.14778/3551793.3551794

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,654 An Experimental Study on Hub Labeling based Shortest Path Algorithms 2018 VLDB 0.000109978
2,639 Scaling Distance Labeling on Small-World Networks 2019 SIGMOD 8.3975113e-05
3,503 FREDE: Anytime Graph Embeddings 2021 VLDB 7.0355661e-05
Previous Page 1 / 1 Next

Semantically Similar Papers