UJM at CLEF in Author Verification based on optimized classification trees

Abstract : This article describes our proposal for the Author Identification task in the PAN CLEF Challenge 2014. We have adopted a machine learning ap- proach based on several representations of the texts and on optimized decision trees which have as entry various attributes and which are learned for every train- ing corpus separately for this classification task. Our method ranked us at the 2nd place with an overall AUC of 70.7%, and C@1 of 68.4% and, between the 1st and the 6th place on the six corpora.
Type de document :
Communication dans un congrès
CLEF 2014, Sep 2014, Sheffield, United Kingdom. 7p., 2014
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https://hal-emse.ccsd.cnrs.fr/emse-01065829
Contributeur : Florent Breuil <>
Soumis le : jeudi 18 septembre 2014 - 15:46:05
Dernière modification le : jeudi 11 janvier 2018 - 06:20:35

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  • HAL Id : emse-01065829, version 1

Citation

Jordan Frery, Christine Largeron, Mihaela Juganaru-Mathieu. UJM at CLEF in Author Verification based on optimized classification trees. CLEF 2014, Sep 2014, Sheffield, United Kingdom. 7p., 2014. 〈emse-01065829〉

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