The Causal-Effect Score in Data Management
Databases
2025-09-23 v4 Artificial Intelligence
Abstract
The Causal Effect (CE) is a numerical measure of causal influence of variables on observed results. Despite being widely used in many areas, only preliminary attempts have been made to use CE as an attribution score in data management, to measure the causal strength of tuples for query answering in databases. In this work, we introduce, generalize and investigate the so-called Causal-Effect Score in the context of classical and probabilistic databases.
Keywords
Cite
@article{arxiv.2502.02495,
title = {The Causal-Effect Score in Data Management},
author = {Felipe Azua and Leopoldo Bertossi},
journal= {arXiv preprint arXiv:2502.02495},
year = {2025}
}
Comments
21 pages. Slightly extended and revised version of published paper in Proc. 4th Conference on Causal Learning and Reasoning (CLeaR), 2025. PMLR 2025, 275:874-893