Projektbeschreibung
Many real-life applications, for example data integration, data extraction, risk-management or sensor systems, naturally produce uncertain data. One of the most important goals in these applications is to produce data of high quality. This leads to the following open questions:
- What does high quality exactly mean with respect to uncertainty and impreciseness?
- What metrics are most qualified for quantifying the quality with respect to these means?
- How to efficiently and effectively detect duplicates, if data are not only unclean but also imprecise and uncertain?
- How to combine the uncertain information given by multiple duplicates so that a tuple of higher quality results?
- How can the expressive modeling power of uncertain data models be used to capture uncertainty coming up during the integration process?
Beteiligte Personen
- Mitarbeiter
- Studentische Mitarbeiter
- Lars Grote
- Wolfram Wingerath
- Steffen Friedrich
- Finn Petersen
Publikationen im Projekt
2012 |
In: The 17th International Conference on Information Quality | |
2011 | ![]() |
In: 5th International Conference on Scalable Uncertainty Management |
In: Ingenierie des Systemes d'Information |
Studentische Arbeiten im Projekt
2014 | ![]() | Masterarbeit von Erik Meyer
|
2012 | ![]() | Diplomarbeit von Lennart Helm
|
![]() | Diplomarbeit von David Haasenleder
| |
Laufend | ![]() ![]() | Masterarbeit von Jennifer Soltau
|
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Am 28. February 2018 um 14:10 von Anne Hansen-AwizenCALL getCollectionFull('research/lookproject','vsis',48,0)