# Classifying Patent Applications with Ensemble Methods

arXiv: https://arxiv.org/abs/1811.04695 · HTML: https://mlsanity.com/paper/1811.04695/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Nov 2018.

## Built on by (most cited first, 2 of 2)

- [A Survey on Patent Analysis: From NLP to Multimodal AI](https://mlsanity.com/paper/2404.08668/) (2024)
- [Automated Single-Label Patent Classification using Ensemble Classifiers](https://mlsanity.com/paper/2203.03552/) (2022)

## Abstract (arXiv)

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.