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Learning and Deducing Temporal Orders

Authors:

Muhammad Asif AliAuthors Info & Claims

Proceedings of the VLDB Endowment, Volume 16, Issue 8

Pages 1944 - 1957

https://doi.org/10.14778/3594512.3594524

Published: 01 April 2023 Publication History

Abstract

This paper studies how to determine temporal orders on attribute values in a set of tuples that pertain to the same entity, in the absence of complete timestamps. We propose a creator-critic framework to learn and deduce temporal orders by combining deep learning and rule-based deduction, referred to as GATE (Get the lATEst). The creator of GATE trains a ranking model via deep learning, to learn temporal orders and rank attribute values based on correlations among the attributes. The critic then validates the temporal orders learned and deduces more ranked pairs by chasing the data with currency constraints; it also provides augmented training data as feedback for the creator to improve the ranking in the next round. The process proceeds until the temporal order obtained becomes stable. Using real-life and synthetic datasets, we show that GATE is able to determine temporal orders with F-measure above 80%, improving deep learning by 7.8% and rule-based methods by 34.4%.

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Cited By

Bao ZBie BFan WLi DLi MLin KLin WLiu PLiu PLv ZOuyang MSun CTang SWang YWei QWu XXie MZhang JZhao RZhu JZhu Y(2024)Rock: Cleaning Data with both ML and Logic RulesProceedings of the VLDB Endowment10.14778/3685800.368587817:12(4373-4376)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.14778/3685800.3685878
Fan WPang KLu PTian C(2024)Making It Tractable to Detect and Correct Errors in GraphsACM Transactions on Database Systems10.1145/370231549:4(1-75)Online publication date: 2-Nov-2024
https://dl.acm.org/doi/10.1145/3702315
Bian LYang WXu JTan ZSerra ESpezzano F(2024)Discovering Denial Constraints Based on Deep Reinforcement LearningProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679714(120-129)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679714

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Information & Contributors

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Published In

cover image Proceedings of the VLDB Endowment

Proceedings of the VLDB Endowment Volume 16, Issue 8

April 2023

257 pages

ISSN:2150-8097

Editors:
Georgia Koutrika
Athena Research Center
,
Jun Yang
Duke University

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VLDB Endowment

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Published: 01 April 2023

Published in PVLDB Volume 16, Issue 8

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Cited By

Bao ZBie BFan WLi DLi MLin KLin WLiu PLiu PLv ZOuyang MSun CTang SWang YWei QWu XXie MZhang JZhao RZhu JZhu Y(2024)Rock: Cleaning Data with both ML and Logic RulesProceedings of the VLDB Endowment10.14778/3685800.368587817:12(4373-4376)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.14778/3685800.3685878
Fan WPang KLu PTian C(2024)Making It Tractable to Detect and Correct Errors in GraphsACM Transactions on Database Systems10.1145/370231549:4(1-75)Online publication date: 2-Nov-2024
https://dl.acm.org/doi/10.1145/3702315
Bian LYang WXu JTan ZSerra ESpezzano F(2024)Discovering Denial Constraints Based on Deep Reinforcement LearningProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679714(120-129)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679714

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