Ontological Pathfinding: Mining First-Order Knowledge from Large Knowledge Bases
Summary: Ontological Pathfinding (OP) scales first-order rule mining to web-scale KBs (Freebase) using parallel batches, a relational KB model, partitioning, and pruning. Mines 36,625 rules in 34 hours; first system to scale to Freebase. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yang Chen (University of Florida)
- 2. Sean Goldberg (University of Florida)
- 3. Daisy Zhe Wang (University of Florida)
- 4. Soumitra Siddharth Johri (University of Florida)
BibTeX Citation
@inproceedings{chen_sigmod16,
title = {{Ontological Pathfinding: Mining First-Order Knowledge from Large Knowledge Bases}},
author = {Chen, Yang and Goldberg, Sean and Wang, Daisy Zhe and Johri, Soumitra Siddharth},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2882954},
url = {https://dl.acm.org/doi/10.1145/2882903.2882954},
year = {2016}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,968 | ArchimedesOne: Query Processing over Probabilistic Knowledge Bases | 2016 | VLDB | 5.7303405e-05 |
| 8,491 | Synthesizing Mapping Relationships Using Table Corpus | 2017 | SIGMOD | 5.414689e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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