With vast amounts of data being accessible more than ever before, organizations are more and more compelled to use the data in a meaningful way to gain an advantage over possible competitors. Data anonymization, which in the context of this work is defined as the redaction of personally identifiable information from the textual data to be legally allowed to process the data and also ensure that no personal information about individuals or organizations occurring in the data is disclosed in any form, of unstructured data is
an increasingly complex challenge. This thesis proposes an anonymization solution for textual support ticket data of an industrial automation company.
Forschungs-