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Computer Science > Databases

arXiv:1208.1932 (cs)
[Submitted on 9 Aug 2012]

Title:Statistical Distortion: Consequences of Data Cleaning

Authors:Tamraparni Dasu, Ji Meng Loh
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Abstract:We introduce the notion of statistical distortion as an essential metric for measuring the effectiveness of data cleaning strategies. We use this metric to propose a widely applicable yet scalable experimental framework for evaluating data cleaning strategies along three dimensions: glitch improvement, statistical distortion and cost-related criteria. Existing metrics focus on glitch improvement and cost, but not on the statistical impact of data cleaning strategies. We illustrate our framework on real world data, with a comprehensive suite of experiments and analyses.
Comments: VLDB2012
Subjects: Databases (cs.DB)
Cite as: arXiv:1208.1932 [cs.DB]
  (or arXiv:1208.1932v1 [cs.DB] for this version)
  https://doi.org/10.48550/arXiv.1208.1932
Journal reference: Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1674-1683 (2012)

Submission history

From: Tamraparni Dasu [view email] [via Ahmet Sacan as proxy]
[v1] Thu, 9 Aug 2012 14:52:19 UTC (547 KB)
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