@inproceedings{bdc798d454e84de0bbf11e7b5145c324,
title = "Local n-grams for author identification: notebook for PAN at CLEF 2013",
abstract = "Our approach to the author identification task uses existing authorship attribution methods using local n-grams (LNG) and performs a weighted ensemble. This approach came in third for this year's competition, using a relatively simple scheme of weights by training set accuracy. LNG models create profiles, consisting of a list of character n-grams that best represent a particular author's writing. The use of a weighted ensemble improved upon the accuracy of the method without reducing the speed of the algorithm; the submitted solution was not only near the top of the leaderboard in terms of accuracy, but it was also one of the faster algorithms submitted.",
author = "Robert Layton and Paul Watters and Richard Dazeley",
year = "2013",
language = "English",
series = "CEUR Workshop Proceedings",
publisher = "CEUR Workshop Proceedings",
editor = "Pamela Forner and Roberto Navigli and Dan Tufis and Nicola Ferro",
booktitle = "Proceedings of the CLEF 2013 conference",
note = "2013 Cross Language Evaluation Forum Conference, CLEF 2013 ; Conference date: 23-09-2013 Through 26-09-2013",
}