Maverick: A System for Discovering Exceptional Facts from Knowledge Graphs
Summary: Maverick employs a beam-search framework to discover exceptional facts about entities in knowledge graphs. Facts are context-subspace pairs (attributes, graph-context) with an end-to-end portal and a shared cache for cross-entity reuse, plus natural-language explanations and charts. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Gensheng Zhang (Google)
- 2. Chengkai Li (University of Texas)
BibTeX Citation
@article{zhang_vldb18,
title = {{Maverick: A System for Discovering Exceptional Facts from Knowledge Graphs}},
author = {Zhang, Gensheng and Li, Chengkai},
journal = {PVLDB},
series = {{VLDB} '18},
volume = {11},
number = {12},
pages = {1934--1937},
doi = {10.14778/3229863.3236228},
url = {https://doi.org/10.14778/3229863.3236228},
year = {2018}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,765 | User Guidance for Efficient Fact Checking | 2019 | VLDB | 5.4558382e-05 |
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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 |
|---|---|---|---|---|
| 4,130 | Computational Journalism: A Call to Arms to Database Researchers | 2011 | CIDR | 6.7874804e-05 |
| 6,443 | Maverick: Discovering Exceptional Facts from Knowledge Graphs | 2018 | SIGMOD | 5.7814657e-05 |
| 7,064 | Data In, Fact Out: Automated Monitoring of Facts by FactWatcher | 2014 | VLDB | 5.6076884e-05 |
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