On the Use of PU Learning for Quality Flaw Prediction in Wikipedia.
RiuNet (Universitat Politècnica de València)Published 1 January 2012Open access
Edgardo Ferretti, Donato Hernández Fusilier, Rafael Guzmán-Cabrera, Manuel Montes-y-Gómez, Marcelo Luis Errecalde, Paolo Rosso
Citations10
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TL;DR
The work of Paolo Rosso was carried out also in the framework of the MICINN Text-Enterprise research project and the Microcluster VLC/Campus (International Campus of Excellence) on Multimodal Intelligent Systems.
Abstract
[EN] In this article we describe a new approach to assess Quality Flaw Prediction in Wikipedia. The partially supervised method studied, called PU Learning, has been successfully applied in classi cations tasks with traditional corpora like Reuters-21578 or 20-Newsgroups. To the best of our knowledge, this is the rst time that it is applied in this domain. Throughout this paper, we describe how the original PU Learning approach was evaluated for assessing quality flaws and the modi cations introduced to get a quality \naws predictor which obtained the best F1 scores in the task \\Quality Flaw Prediction in Wikipedia" of the PAN challenge.
Keywords
Social SciencesComputer Science
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