Year: 2025
Type: article
Abstract: Managing the vast amount of text data in the digital world is a complex challenge. An effective approach to tackle it is through the technique of text document clustering. This study evaluated the performance of three clustering algorithms — K-Means, Single Linkage, and Gaussian Mixture Model (GMM) — in clustering Brazilian Portuguese news articles using BERTimBau, a Portuguese variant of the BERT model, for preprocessing. Metrics such as accuracy, F1-score, Rand index, and Jaccard coefficient were used for evaluation. The results of these metrics indicated that Single Linkage achieved the best overall performance, surpassing K-Means and GMM in most of the evaluated criteria.
Author: Beatriz Ribeiro Borges
Institution: Universidade Federal de Uberlândia
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409109871