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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Beskales, G. Ilyas, I.F. Golab, L. Galiullin, A. |
| Copyright Year | 2013 |
| Description | Author affiliation: Qatar Comput. Res. Inst., Qatar (Beskales, G.; Ilyas, I.F.) |
| Abstract | Functional dependencies (FDs) specify the intended data semantics while violations of FDs indicate deviation from these semantics. In this paper, we study a data cleaning problem in which the FDs may not be completely correct, e.g., due to data evolution or incomplete knowledge of the data semantics. We argue that the notion of relative trust is a crucial aspect of this problem: if the FDs are outdated, we should modify them to fit the data, but if we suspect that there are problems with the data, we should modify the data to fit the FDs. In practice, it is usually unclear how much to trust the data versus the FDs. To address this problem, we propose an algorithm for generating non-redundant solutions (i.e., simultaneous modifications of the data and the FDs) corresponding to various levels of relative trust. This can help users determine the best way to modify their data and/or FDs to achieve consistency. |
| Sponsorship | IEEE Comput. Soc. |
| Starting Page | 541 |
| Ending Page | 552 |
| File Size | 673770 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781467349093 |
| ISSN | 10636382 |
| e-ISBN | 9781467349109 |
| e-ISBN | 9781467349086 |
| DOI | 10.1109/ICDE.2013.6544854 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-04-08 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Maintenance engineering Optimized production technology Semantics Approximation algorithms Cleaning Measurement Vectors |
| Content Type | Text |
| Resource Type | Article |
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