  We present here our approach to the GermEval 2019 Task 1 - Shared Task on
hierarchical classification of German blurbs. We achieved first place in the
hierarchical subtask B and second place on the root node, flat classification
subtask A. In subtask A, we applied a simple multi-feature TF-IDF extraction
method using different n-gram range and stopword removal, on each feature
extraction module. The classifier on top was a standard linear SVM. For the
hierarchical classification, we used a local approach, which was more
light-weighted but was similar to the one used in subtask A. The key point of
our approach was the application of a post-processing to cope with the
multi-label aspect of the task, increasing the recall but not surpassing the
precision measure score.
