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Aggregate query processing on incomplete data

  • Anzhen Zhang*
  • , Jinbao Wang
  • , Jianzhong Li
  • , Hong Gao
  • *Corresponding author for this work
  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Incomplete data has been a longstanding issue in database community, and yet the subject is poorly handled by both theory and practice. In this paper, we propose to directly estimate the aggregate query result on incomplete data, rather than imputing the missing values. An interval estimation, composed of the upper and lower bound of aggregate query results among all possible interpretation of missing values, are presented to the end-users. The ground-truth aggregate result is guaranteed to be among the interval. Experimental results are consistent with the theoretical results, and suggest that the estimation is invaluable to better assess the results of aggregate queries on incomplete data.

Original languageEnglish
Title of host publicationWeb and Big Data - Second International Joint Conference, APWeb-WAIM 2018, Proceedings
EditorsJianliang Xu, Yoshiharu Ishikawa, Yi Cai
PublisherSpringer Verlag
Pages286-294
Number of pages9
ISBN (Print)9783319968896
DOIs
StatePublished - 2018
Event2nd Asia Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data, APWeb-WAIM 2018 - Macau, China
Duration: 23 Jul 201825 Jul 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10987 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd Asia Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data, APWeb-WAIM 2018
Country/TerritoryChina
CityMacau
Period23/07/1825/07/18

Keywords

  • Aggregate query
  • Estimation
  • Incomplete data

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