Título: Sentiment Analysis of Restaurant Reviews in Portuguese A transfer learning and ensemble approach with edge computing
Autor: Alexandre João Jardim Branco
Local: Sala 2.109 da FCCE e sessão Zoom https://videoconf-colibri.zoom.us/j/92546480682
Dia/Hora: 05/02/2024 às 16:00
Abstract
This research focuses on improving sentiment analysis in restaurant reviews by leveraging transfer learning and transformer-based pre-trained models. Specifically, we employ BERT and RoBERTa, two state-of-the-art models, to build a sentiment review classifier. The classifier’s performance is evaluated using accuracy and AUC ROC as the primary metrics. Our results demonstrate that the classifier developed using ensemble techniques outperforms the baseline model in accurately classifying restaurant reviews. This research contributes to sentiment analysis by exploring the effectiveness of transfer learning and transformer-based models in the context of Portuguese restaurant reviews.
This work highlights the importance of considering the Portuguese language in sentiment analysis tasks. Furthermore, this study investigates the deployment of the model on edge computing platforms, making sentiment analysis more accessible in resource-constrained environments. Combining deep learning techniques, transfer learning, and edge computing offers promising real-time sentiment analysis application opportunities. This research provides valuable insights for researchers and practitioners interested in sentiment analysis, natural language processing, and text analysis in the context of restaurant reviews.
Keywords: Sentiment analysis, natural language processing, Portuguese language, edge-computing, transfer-learning, transformers.