Authorship Verification with neural networks via stylometric feature concatenation

In the authorship verification task (PAN at CLEF 2021) the main aim is to discriminate between pairs of texts written by the same author or by two different authors. Our work focuses on extracting two stylometric features, character-level n-grams and the use of punctuation marks in the texts. Subsequently, we train a neural network with each of them and finally combine them into a final neural network for the classifier decision making.

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