Banzhaf Values for Facts in Query Answering

Author:

Abramovich Omer1ORCID,Deutch Daniel1ORCID,Frost Nave2ORCID,Kara Ahmet3ORCID,Olteanu Dan3ORCID

Affiliation:

1. Tel Aviv University, Tel Aviv, Israel

2. eBay, Tel Aviv, Israel

3. University of Zurich, Zurich, Switzerland

Abstract

Quantifying the contribution of database facts to query answers has been studied as means of explanation. The Banzhaf value, originally developed in Game Theory, is a natural measure of fact contribution, yet its efficient computation for select-project-join-union queries is challenging. In this paper, we introduce three algorithms to compute the Banzhaf value of database facts: an exact algorithm, an anytime deterministic approximation algorithm with relative error guarantees, and an algorithm for ranking and top-k. They have three key building blocks: compilation of query lineage into an equivalent function that allows efficient Banzhaf value computation; dynamic programming computation of the Banzhaf values of variables in a Boolean function using the Banzhaf values for constituent functions; and a mechanism to compute efficiently lower and upper bounds on Banzhaf values for any positive DNF function. We complement the algorithms with a dichotomy for the Banzhaf-based ranking problem: given two facts, deciding whether the Banzhaf value of one is greater than of the other is tractable for hierarchical queries and intractable for non-hierarchical queries. We show experimentally that our algorithms significantly outperform exact and approximate algorithms from prior work, most times up to two orders of magnitude. Our algorithms can also cover challenging problem instances that are beyond reach for prior work.

Funder

UZH Global Strategy and Partnerships Funding Scheme

European Research Council

Publisher

Association for Computing Machinery (ACM)

Reference55 articles.

1. Serge Abiteboul, Richard Hull, and Victor Vianu. 1995. Foundations of Databases. Vol. 8. Addison-Wesley Reading. http://webdam.inria.fr/Alice/

2. Omer Abramovich Daniel Deutch Nave Frost Ahmet Kara and Dan Olteanu. 2023 a. Banzhaf Values for Facts in Query Answering. arxiv: 2308.05588 [cs.DB] Extended Version.

3. Omer Abramovich Daniel Deutch Nave Frost Ahmet Kara and Dan Olteanu. 2023 b. GitHub Repository. https://github.com/Omer-Abramovich/AdaBan.

4. LearnShapley: Learning to Predict Rankings of Facts Contribution Based on Query Logs

5. The Tractability of SHAP-Score-Based Explanations for Classification over Deterministic and Decomposable Boolean Circuits

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Generalized Causal-Effect Score in Data Management (short paper);Proceedings of the Conference on Governance, Understanding and Integration of Data for Effective and Responsible AI;2024-06-09

2. Expected Shapley-Like Scores of Boolean functions: Complexity and Applications to Probabilistic Databases;Proceedings of the ACM on Management of Data;2024-05-10

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3