The Shapley Value in Database Management

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Bertossi, Leopoldo, Kimelfeld, Benny, Livshits, Ester, Monet, Mikaël
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866910295075586048
author Bertossi, Leopoldo
Kimelfeld, Benny
Livshits, Ester
Monet, Mikaël
author_facet Bertossi, Leopoldo
Kimelfeld, Benny
Livshits, Ester
Monet, Mikaël
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2401_06234
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle The Shapley Value in Database Management
Bertossi, Leopoldo
Kimelfeld, Benny
Livshits, Ester
Monet, Mikaël
Databases
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.
title The Shapley Value in Database Management
topic Databases
url https://arxiv.org/abs/2401.06234