Web-ADARE

A web-aided data repairing system

Binbin Gu, Zhixu Li*, Qiang Yang, Qing Xie, An Liu, Guanfeng Liu, Kai Zheng, Xiangliang Zhang

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Data repairing aims at discovering and correcting erroneous data in databases. In this paper, we develop Web-ADARE, an end-to-end web-aided data repairing system, to provide a feasible way to involve the vast data sources on the Web in data repairing. Our main attention in developing Web-ADARE is paid on the interaction problem between web-aided repairing and rule-based repairing, in order to minimize the Web consultation cost while reaching predefined quality requirements. The same interaction problem also exists in crowd-based methods but this is not yet formally defined and addressed. We first prove in theory that the optimal interaction scheme is not feasible to be achieved, and then propose an algorithm to identify a scheme for efficient interaction by investigating the inconsistencies and the dependencies between values in the repairing process. Extensive experiments on three data collections demonstrate the high repairing precision and recall of Web-ADARE, and the efficiency of the generated interaction scheme over several baseline ones.

Original languageEnglish
Pages (from-to)201-214
Number of pages14
JournalNeurocomputing
Volume253
DOIs
Publication statusPublished - Aug 2017
Externally publishedYes

Keywords

  • Data repairing
  • Multiple sources
  • Rule-based method
  • Web-aided method

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