GRN Model of Probabilistic Databases: Construction, Transition and Querying
Summary: Proposes Generator-Recognizer Network (GRN) as a tuple-level uncertainty model for probabilistic databases, enabling richer dependency representations than prior formalisms. Defines constraint- and query-induced transitions that preserve GRN form, delivering a closed, self-contained framework with a systematic construction path and improved query evaluation. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Ruiwen Chen
- 2. Yongyi Mao
- 3. Iluju Kiringa
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| 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 |
| 477 | Model-Driven Data Acquisition in Sensor Networks | 2004 | VLDB | 0.00022221803 |
| 560 | Dependencies Revisited for Improving Data Quality | 2008 | PODS | 0.00020141923 |
| 571 | The Complexity of Query Reliability | 1998 | PODS | 0.00019910719 |
| 627 | Management of Probabilistic Data: Foundations and Challenges | 2007 | PODS | 0.00018959005 |
| 721 | Data Integration with Uncertainty | 2007 | VLDB | 0.00017570539 |
| 760 | Creating Probabilistic Databases from Information Extraction Models | 2006 | VLDB | 0.00017053935 |
| 1,730 | Conditioning Probabilistic Databases | 2008 | VLDB | 0.00010736755 |
| 2,796 | Hypertree Decompositions and Tractable Queries | 1999 | PODS | 8.1112658e-05 |
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