  We explore the abilities of character recurrent neural network (char-RNN) for
hashtag segmentation. Our approach to the task is the following: we generate
synthetic training dataset according to frequent n-grams that satisfy
predefined morpho-syntactic patterns to avoid any manual annotation. The active
learning strategy limits the training dataset and selects informative training
subset. The approach does not require any language-specific settings and is
compared for two languages, which differ in inflection degree.
