Name
Abstract | ||
|---|---|---|
Digitization brings about new ways of analyzing data from cultural heritage areas. Automatic error detection, as input to semiautomatic error correction, is one type of analysis that can be found high on the priority list of cultural heritage data managers and researchers. We describe a general approach to cleaning cultural heritage databases. We present four case studies on databases from different cultural heritage institutions, and describe an information system in which we embed our error detector in a larger framework, enabling researchers to access, check, and correct their data more easily than before. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/MIS.2009.33 | IEEE Intelligent Systems |
Keywords | Field | DocType |
machine learning,cultural differences,classification algorithms,database management systems,humanities,probability density function,databases,data mining,learning artificial intelligence,cultural heritage | Data mining,Cultural heritage,Computer science,Industrial heritage,Cultural heritage management,Cultural diversity | Journal |
Volume | Issue | ISSN |
24 | 2 | 1541-1672 |
Citations | PageRank | References |
3 | 0.47 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antal Van Den Bosch | 1 | 1038 | 132.37 |
| Marieke van Erp | 2 | 284 | 24.19 |
| Caroline Sporleder | 3 | 453 | 31.84 |