Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS
Summary: Bottom-up grounding leverages the RDBMS optimizer to scale MLN grounding. Hybrid AI/DBMS architecture enables local search inside the DBMS, with partitioning and parallel loading that deliver faster, higher-quality MLN inference than prior systems. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Feng Niu
- 2. Christopher RĂ©
- 3. AnHai Doan
- 4. Jude Shavlik
Incoming Citations (Sorted by Pagerank)
Showing 23 of 23 citing papers.
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Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 74 | Efficient Query Evaluation on Probabilistic Databases | 2004 | VLDB | 0.00057857292 |
| 321 | MCDB: A Monte Carlo Approach to Managing Uncertain Data | 2008 | SIGMOD | 0.00027527389 |
| 469 | MauveDB: Supporting Model-based User Views in Database Systems | 2006 | SIGMOD | 0.00022406923 |
| 980 | BayesStore: Managing Large, Uncertain Data Repositories with Probabilistic Graphical Models | 2008 | VLDB | 0.00014879747 |
| 3,398 | Event Queries on Correlated Probabilistic Streams | 2008 | SIGMOD | 7.141911e-05 |
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