title: Fast & Confident Probabilistic Categorization
creator: Goutte, Cyril
subject: Statistical Models
subject: Computational Linguistics
subject: Machine Learning
description: We describe NRC's submission to the Anomaly Detection/Text Mining competition organised at the Text Mining Workshop 2007.  This submission relies on a straightforward implementation of the probabilistic categoriser described in (Gaussier et al., ECIR'02).  This categoriser is adapted to handle multiple labelling and a piecewise-linear confidence estimation layer is added to provide an estimate of the labelling confidence.  This technique achieves a score of 1.689 on the test data. 
date: 2007
type: Conference Paper
type: NonPeerReviewed
format: application/pdf
identifier: http://cogprints.org/5626/1/goutte07tmw.pdf
identifier:   Goutte, Cyril  (2007) Fast & Confident Probabilistic Categorization.  [Conference Paper]     
relation: http://cogprints.org/5626/