Publication type: Conference paper
Type of review: Not specified
Title: Classifying patent applications with ensemble methods
Authors: Benites de Azevedo e Souza, Fernando
Malmasi, Shervin
Zampieri, Marcos
Proceedings: Australasian language technology association workshop 2018 : proceedings of the workshop
Volume(Issue): 16
Pages: 89
Pages to: 92
Conference details: 16th Annual Workshop of The Australasian Language Technology Association (ALTA 2018), Dunedin, New Zealand, 10-12 December 2018
Issue Date: 2018
Publisher / Ed. Institution: Australasian Language Technology Association
ISSN: 1834-7037
Language: English
Subject (DDC): 005: Computer programming, programs and data
020: Library and information sciences
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.
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Appears in Collections:Publikationen School of Engineering

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