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Probabilistic Reasoning at Scale: Trigger Graphs to the Rescue

Summary: Extends Trigger Graphs to probabilistic reasoning with possible-world semantics while avoiding lineage materialization. LTGs enable scalable probabilistic DB reasoning by grouping derivations, outperforming engines and handling larger uncertain data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6542
Venue
SIGMOD
Year
2023
Pagerank
4.1945683e-05
Overall Rank
11,179 | 22.23%
DOI
10.1145/3588719

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Showing 14 of 14 cited papers.

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

Rank Cited Paper Year Venue Pagerank
16 MAGIC SETS AND OTHER STRANGE WAYS TO IMPLEMENT LOGIC PROGRAMS (Extended Abstract) 1986 PODS 0.0010066783
31 Provenance Semirings 2007 PODS 0.0007857786
667 Incremental Knowledge Base Construction Using DeepDive 2015 VLDB 0.00018440557
698 The Chase Revisited 2008 PODS 0.00018030148
804 YAGO3: A Knowledge Base from Multilingual Wikipedias 2015 CIDR 0.00016463579
1,066 Probase: A Probabilistic Taxonomy for Text Understanding 2012 SIGMOD 0.0001433416
1,268 The Dichotomy of Conjunctive Queries on Probabilistic Structures 2007 PODS 0.00012931993
1,970 Approximate Lineage for Probabilistic Databases 2008 VLDB 9.896375e-05
3,004 Benchmarking the Chase 2017 PODS 7.7314538e-05
4,164 SlimShot: In-Database Probabilistic Inference for Knowledge Bases 2016 VLDB 6.3923099e-05
4,521 A Temporal-Probabilistic Database Model for Information Extraction 2013 VLDB 6.1168322e-05
5,165 The Vadalog System: Datalog-based Reasoning for Knowledge Graphs 2018 VLDB 5.6529675e-05
8,581 Anytime Approximation in Probabilistic Databases via Scaled Dissociations 2019 SIGMOD 4.492241e-05
9,714 Materializing Knowledge Bases via Trigger Graphs 2021 VLDB 4.299267e-05
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