Projects per year
Abstract
A variety of dependency formalisms have been studied for improving data quality. To treat these dependencies in a uniform framework, we propose a simple language, Quality Improving Dependencies (QIDs). We show that previous dependencies considered for data quality can be naturally expressed as
QIDs, and that different enforcement mechanisms of QIDs yield various data repairing strategies.
QIDs, and that different enforcement mechanisms of QIDs yield various data repairing strategies.
Original language | English |
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Pages (from-to) | 34-42 |
Number of pages | 9 |
Journal | IEEE Data Engineering Bulletin |
Volume | 34 |
Issue number | 3 |
Publication status | Published - 2011 |
Projects
- 1 Finished
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Heterogeneous and Permanent data
Buneman, P., Fan, W., Libkin, L. & Viglas, S.
1/03/08 → 29/02/12
Project: Research