Kontextsensitive Entscheidungsfindung zur automatisierten Identifizierung und Clusterung deutschsprachiger Urbanonyme

Many historical sources contain numerous names of places, the manual assignment of which ties up a lot of resources. To simpliy this, an algorithm is described with which such urbanonyms can be geocoded automatically. It is also possible to cluster the places according to their common historical administrative affiliation. Problems such as identical terms for place names are solved primarily by including further information from the same context (same source). A validation is done on the basis of about 3.4 million mostly German-language place names from the genealogical database GEDBAS. In summary, about three out of four relevant place names can be identified and localised. More than 90 percent of the identified place names can be assigned to their historical province