# The Shapley Value in Database Management

arXiv: https://arxiv.org/abs/2401.06234 · HTML: https://mlsanity.com/paper/2401.06234/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jan 2024.

## Built on by (most cited first, 11 of 11)

- [SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelism](https://mlsanity.com/paper/2510.21599/) (2025)
- [Expected Shapley-Like Scores of Boolean Functions: Complexity and Applications to Probabilistic Databases](https://mlsanity.com/paper/2401.06493/) (2024)
- [Shapley Value Computation in Ontology-Mediated Query Answering](https://mlsanity.com/paper/2407.20058/) (2024)
- [Concorde: Fast and Accurate CPU Performance Modeling with Compositional Analytical-ML Fusion](https://mlsanity.com/paper/2503.23076/) (2025)
- [A Comprehensive Study of Shapley Value in Data Analytics](https://mlsanity.com/paper/2412.01460/) (2024)
- [Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach](https://mlsanity.com/paper/2504.16668/) (2025)
- [The Causal-Effect Score in Data Management](https://mlsanity.com/paper/2502.02495/) (2025)
- [Causality-Based Scores Alignment in Explainable Data Management](https://mlsanity.com/paper/2503.14469/) (2025)
- [The Sets of Power](https://mlsanity.com/paper/2410.07867/) (2024)
- [Data Acquisition for Improving Model Fairness using Reinforcement Learning](https://mlsanity.com/paper/2412.03009/) (2024)
- [RelShap: Relationally Consistent Shapley Explanations](https://mlsanity.com/paper/2608.11508/) (2026)

## Abstract (arXiv)

Attribution scores can be applied in data management to quantify the contribution of individual items to conclusions from the data, as part of the explanation of what led to these conclusions. In Artificial Intelligence, Machine Learning, and Data Management, some of the common scores are deployments of the Shapley value, a formula for profit sharing in cooperative game theory. Since its invention in the 1950s, the Shapley value has been used for contribution measurement in many fields, from economics to law, with its latest researched applications in modern machine learning. Recent studies investigated the application of the Shapley value to database management. This article gives an overview of recent results on the computational complexity of the Shapley value for measuring the contribution of tuples to query answers and to the extent of inconsistency with respect to integrity constraints. More specifically, the article highlights lower and upper bounds on the complexity of calculating the Shapley value, either exactly or approximately, as well as solutions for realizing the calculation in practice.