Learning and Deducing Temporal Orders
Summary: Infers temporal orders of same-entity attribute values without full timestamps via GATE: a creator–critic loop that couples a deep-ranking model with rule-based currency deduction. The critic validates/deduces extra ordered pairs and feeds augmented labels back until convergence, boosting F‑measure (>80%) and outperforming pure deep learning and rule baselines. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Wenfei Fan (Beihang University; Shenzhen University; University of Edinburgh)
- 2. Resul Tugay (University of Edinburgh)
- 3. Yaoshu Wang (Shenzhen University)
- 4. Min Xie (Shenzhen University)
- 5. Muhammad Asif Ali (King Abdullah University of Science and Technology)
BibTeX Citation
@article{fan_vldb23,
title = {{Learning and Deducing Temporal Orders}},
author = {Fan, Wenfei and Tugay, Resul and Wang, Yaoshu and Xie, Min and Ali, Muhammad Asif},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {8},
pages = {1944--1957},
doi = {10.14778/3594512.3594524},
url = {https://doi.org/10.14778/3594512.3594524},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,872 | Rock: Cleaning Data by Embedding ML in Logic Rules | 2024 | SIGMOD | 5.4362062e-05 |
| 11,635 | Rock: Cleaning Data with both ML and Logic Rules | 2024 | VLDB | 4.9793485e-05 |
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Showing 15 of 15 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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