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Graph-Based Siamese Network for Authorship Verification
2022
Mathematics
In this work, we propose a novel approach to solve the authorship identification task on a cross-topic and open-set scenario. Authorship verification is the task of determining whether or not two texts were written by the same author. We model the documents in a graph representation and then a graph neural network extracts relevant features from these graph representations. We present three strategies to represent the texts as graphs based on the co-occurrence of the POS labels of words. We
doi:10.3390/math10020277
fatcat:b45k7hhb6fgjpioku74d6tnrai