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Algorithms for Computing Approximate Certain Answers over Incomplete Databases

Published: 18 June 2018 Publication History

Abstract

Incomplete information arises in many database applications, such as data integration, data exchange, inconsistency management, data cleaning, ontological reasoning, and many others. A principled way of answering queries over incomplete databases is to compute certain answers, which are query answers that can be obtained from every complete database represented by an incomplete one.
For databases containing (labeled) nulls, certain answers to positive queries can be easily computed in polynomial time, but for more general queries with negation the problem becomes coNP-hard. To make query answering feasible in practice, one might resort to SQL's evaluation, but unfortunately, the way SQL behaves in the presence of nulls may result in wrong answers.
Thus, on the one hand, SQL's evaluation is efficient but flawed, on the other hand, certain answers are a principled semantics but with high complexity.
To deal with issue, recent research has focused on developing polynomial time approximation algorithms for computing (approximate) certain answers. This paper surveys recent advances in this area.

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cover image ACM Other conferences
IDEAS '18: Proceedings of the 22nd International Database Engineering & Applications Symposium
June 2018
328 pages
ISBN:9781450365277
DOI:10.1145/3216122
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • Concordia University: Concordia University

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Publication History

Published: 18 June 2018

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Author Tags

  1. Incomplete database
  2. approximation algorithm
  3. certain query answer

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IDEAS 2018

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Overall Acceptance Rate 74 of 210 submissions, 35%

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Cited By

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  • (2022)Intelligent data integration from heterogeneous relational databases containing incomplete and uncertain informationIntelligent Data Analysis10.3233/IDA-20553526:1(75-99)Online publication date: 14-Jan-2022
  • (2022)Performance Appraisal Information System for Intelligent HRM Based on SQL and Data Complexity Estimation2022 International Conference on Electronics and Renewable Systems (ICEARS)10.1109/ICEARS53579.2022.9752431(1620-1623)Online publication date: 16-Mar-2022
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  • (2019)Approximation algorithms for querying incomplete databasesInformation Systems10.1016/j.is.2019.03.010Online publication date: Apr-2019

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