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Towards Event Prediction in Temporal Graphs

Summary: TACOs: temporal association rules over graph updates for event prediction. TASTE uses a creator–critic ML loop to discover TACOs (with ML predicates); shows SAT/implication/prediction complexity and 31.4x faster discovery with 23.4% accuracy gains. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12687
Venue
VLDB
Year
2022
Pagerank
5.5727796e-05
Overall Rank
7,961 | 44.68%
DOI
10.14778/3538598.3538608

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Showing 6 of 6 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,031 Efficient Subgraph Matching: Harmonizing Dynamic Programming, Adaptive Matching Order, and Failing Set Together 2019 SIGMOD 0.00012615956
1,039 YAGO3: A Knowledge Base from Multilingual Wikipedias 2015 CIDR 0.00012571479
1,077 GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph 2014 VLDB 0.00012403698
2,286 Dependencies for Graphs 2017 PODS 8.8854622e-05
6,979 Discovering Graph Functional Dependencies 2018 SIGMOD 5.7927251e-05
7,981 Capturing Associations in Graphs 2020 VLDB 5.5692809e-05
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