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2012
Conference Paper
Titel

Kernel methods and string kernels for authorship analysis

Titel Supplements
Notebook for PAN at CLEF 2012
Abstract
This paper presents our approach to the PAN 2012 Traditional Authorship Attribution tasks and the Sexual Predator Identification task. We approached these tasks with machine learning methods that work at the character level. More precisely, we treated texts as just sequences of symbols (strings) and used string kernels in conjunction with different kernel-based learning methods: supervised and unsupervised. The results were extremely good, we ranked first in most problem and overall in the traditional authorship attribution task, according to the evaluation provided by the organizers.
Author(s)
Popescu, Marius
Grozea, Cristian
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS
Hauptwerk
CLEF 2012 Conference and Labs of the Evaluation Forum. Evaluation Labs and Workshop. Online Working Notes
Konferenz
International Conference of the Cross-Language Evaluation Forum (CLEF) 2012
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Externer Link
Externer Link
Language
English
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Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS
Tags
  • authorship analysis

  • natural language processing

  • string kernels

  • kernel methods

  • machine learning

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