Char-RNN and Active Learning for Hashtag Segmentation

Taisiya Glushkova; Ekaterina Artemova

doi:10.1007/978-3-031-24337-0_12

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arXiv · 1911.03270

Char-RNN and Active Learning for Hashtag Segmentation

Taisiya Glushkova·Ekaterina Artemova

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Abstract

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.

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Taisiya Glushkova, Ekaterina Artemova. 2019-11-08. Char-RNN and Active Learning for Hashtag Segmentation. https://doi.org/10.1007/978-3-031-24337-0_12

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