Statistical Distortion: Consequences of Data Cleaning
Summary: Introduces statistical distortion as a metric for data cleaning impact. A scalable experimental framework evaluates glitch improvement, statistical distortion, and cost, addressing gaps in existing metrics; demonstrated on real-world data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Tamraparni Dasu (AT&T)
- 2. Ji Meng Loh (AT&T)
BibTeX Citation
@article{dasu_vldb12,
title = {{Statistical Distortion: Consequences of Data Cleaning}},
author = {Dasu, Tamraparni and Loh, Ji Meng},
journal = {PVLDB},
series = {{VLDB} '12},
volume = {5},
number = {11},
pages = {1674--1683},
doi = {10.14778/2350229.2350276},
url = {https://doi.org/10.14778/2350229.2350276},
year = {2012}
}
Incoming Citations (Sorted by Pagerank)
Showing 11 of 11 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 549 | ERACER: A Database Approach for Statistical Inference and Data Cleaning | 2010 | SIGMOD | 0.00016692839 |
| 3,052 | Online Data Fusion | 2011 | VLDB | 7.8105426e-05 |
| 4,059 | GDR: A System for Guided Data Repair | 2010 | SIGMOD | 6.9330647e-05 |
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