License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ICDT.2020.20
URN: urn:nbn:de:0030-drops-119442
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Livshits, Ester ; Bertossi, Leopoldo ; Kimelfeld, Benny ; Sebag, Moshe

The Shapley Value of Tuples in Query Answering

LIPIcs-ICDT-2020-20.pdf (0.6 MB)


We investigate the application of the Shapley value to quantifying the contribution of a tuple to a query answer. The Shapley value is a widely known numerical measure in cooperative game theory and in many applications of game theory for assessing the contribution of a player to a coalition game. It has been established already in the 1950s, and is theoretically justified by being the very single wealth-distribution measure that satisfies some natural axioms. While this value has been investigated in several areas, it received little attention in data management. We study this measure in the context of conjunctive and aggregate queries by defining corresponding coalition games. We provide algorithmic and complexity-theoretic results on the computation of Shapley-based contributions to query answers; and for the hard cases we present approximation algorithms.

BibTeX - Entry

  author =	{Ester Livshits and Leopoldo Bertossi and Benny Kimelfeld and Moshe Sebag},
  title =	{{The Shapley Value of Tuples in Query Answering}},
  booktitle =	{23rd International Conference on Database Theory (ICDT 2020)},
  pages =	{20:1--20:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-139-9},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{155},
  editor =	{Carsten Lutz and Jean Christoph Jung},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-119442},
  doi =		{10.4230/LIPIcs.ICDT.2020.20},
  annote =	{Keywords: Shapley value, query answering, conjunctive queries, aggregate queries}

Keywords: Shapley value, query answering, conjunctive queries, aggregate queries
Collection: 23rd International Conference on Database Theory (ICDT 2020)
Issue Date: 2020
Date of publication: 11.03.2020
Supplementary Material: Video of the Presentation:

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