  As a result of transformation processes, the German labor market is highly
dependent on vocational training, retraining and continuing education. To match
training seekers and offers, we present a novel approach towards the automated
detection of access to education and training in German training offers and
advertisements. We will in particular focus on (a) general school and education
degrees and schoolleaving certificates, (b) professional experience, (c) a
previous apprenticeship and (d) a list of skills provided by the German Federal
Employment Agency. This novel approach combines several methods: First, we
provide a mapping of synonyms in education combining different qualifications
and adding deprecated terms. Second, we provide a rule-based matching to
identify the need for professional experience or apprenticeship. However, not
all access requirements can be matched due to incompatible data schemata or
non-standardizes requirements, e.g initial tests or interviews. While we can
identify several shortcomings, the presented approach offers promising results
for two data sets: training and re-training advertisements.
