A recurrent neural network (RNN) is used to model the language of several authors concurrently, with each author's text being represented by separate outputs that rely on a shared recurrent state. This allows the recurrent layer to model the language as a whole without over-fitting even with very small corpora. The method was developed for the PAN 2015 Author Identification task, where it performed well, coming first overall with an average AUC greater than .80.
REF uses a recurrent neural network (RNN) based model for the author identification task.
Author Identification using Multi-headed Recurrent Neural Networks
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Computer Science