@InProceedings{Benites:Malmasi:Zampieri:2018:ALTA2018,
author	 = {Benites, Fernando and Malmasi, Shervin and Zampieri, Marcos},
title		 = {Classifying Patent Applications with Ensemble Methods},
booktitle = {Proceedings of the Australasian Language Technology Association Workshop 2018},
month	 = {December},
year		 = {2018},
address	 = {Dunedin, New Zealand},
pages	 = {89--92},
abstract  = {We present methods for the automatic classification of patent applications using an annotated dataset provided by the organizers of the ALTA 2018 shared task - Classifying Patent Applications. The goal of the task is to use computational methods to categorize patent applications according to a coarse-grained taxonomy of eight classes based on the International Patent Classification (IPC). We tested a variety of approaches for this task and the best results, 0.778 micro-averaged F1-Score, were achieved by SVM ensembles using a combination of words and characters as features. Our team, BMZ, was ranked first among 14 teams in the competition.},
url			 = {http://www.aclweb.org/anthology/U18-1012}
}