A comparison of several AI techniques for authorship attribution on Romanian texts

• URL: http://arxiv.org/abs/2211.05180v1
• Date: Wed, 9 Nov 2022 20:24:48 GMT
• Title: A comparison of several AI techniques for authorship attribution on Romanian texts
• Authors: Sanda Maria Avram and Mihai Oltean
• Abstract summary: We compare AI techniques for classifying literary texts written by multiple authors. We also introduce a new dataset composed of texts written in the Romanian language on which we have run the algorithms.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Determining the author of a text is a difficult task. Here we compare multiple AI techniques for classifying literary texts written by multiple authors by taking into account a limited number of speech parts (prepositions, adverbs, and conjunctions). We also introduce a new dataset composed of texts written in the Romanian language on which we have run the algorithms. The compared methods are Artificial Neural Networks, Support Vector Machines, Multi Expression Programming, Decision Trees with C5.0, and k-Nearest Neighbour. Numerical experiments show, first of all, that the problem is difficult, but some algorithms are able to generate decent errors on the test set.

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