Local n-grams for author identification: Notebook for PAN at CLEF 2013 C3 - CEUR Workshop Proceedings

Title: Local n-grams for author identification: Notebook for PAN at CLEF 2013 C3 - CEUR Workshop Proceedings
Creator: Layton, Robert; Watters, Paul; Dazeley, Richard
Date: 2013
Type: Text; Conference proceedings
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/76647
Identifier: vital:7582
Identifier: http://ceur-ws.org/Vol-1179/CLEF2013wn-PAN-LaytonEt2013.pdf
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.
Publisher: CEUR-WS
Rights: Open access
Rights: This metadata is freely available under a CCO license
Subject: Author identification; Authorship attribution; N-grams; Simple schemes; Training sets
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