Author verification using syntactic N-grams

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Resumen

This paper describes our approach to tackle the Author Verification task at PAN 2015. Our method builds a representation of an author's style by using the information contained in dependency trees. This information is represented as syntactic n-grams and used to conform a vector space. Using unsupervised machine learning approach, each instance is associated to the correponding author using the Jaccard distance. In this paper, we describe the features that were used and the employed unsupervised machine learning algorithm.

Idioma originalInglés
PublicaciónCEUR Workshop Proceedings
Volumen1391
EstadoPublicada - 2015
Evento16th Conference and Labs of the Evaluation Forum, CLEF 2015 - Toulouse, Francia
Duración: 8 sep. 201511 sep. 2015

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