Classifying Patent Applications with Ensemble Methods

2018-11-12 · ALTA 2018 12 · Fernando Benites, Shervin Malmasi, Marcos Zampieri

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.

📄 PDF Abstract BibTeX arXiv:1811.04695

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Classification General ClassificationPatent classification

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