This talk will present the challenges for the research area known as aspect-based sentiment analysis. Sentiment Analysis (or Opinion Mining) is a field of study in Natural Language Processing that aims to extract and classify the sentiment orientation present in texts. Aspect-based Sentiment Analysis (ABSA) is a particular study of sentiment analysis focusing in the extraction of opinions directed to a specific target or aspect.
ABSA has gained a lot of attention and was popularized in the academic field with a dedicated shared task in the last three SemEval workshops (semantic evaluation competition). This talk will present the actual challenges and how are the state-of-art in terms of machine learning algorithms.
Challenges in Aspect-based Sentiment Analysis
July 12, 2016
1:00 pm
Pedro Balage
Pedro Balage is a researcher at Priberam and a PhD student from the University of São Paulo with his topic on Aspect-based Sentiment Analysis. Pedro got his masters in Computational Linguistics by the program Erasmus Mundus International Masters in Natural Language Processing.PriberamSeminários
Últimos seminários
Unlocking Latent Discourse Translation in LLMs Through Quality-Aware Decoding
June 17, 2025Large language models (LLMs) have emerged as strong contenders in machine translation. Yet, they often fall behind specialized neural machine…
Speech as a Biomarker for Disease Detection
May 20, 2025Today’s overburdened health systems face numerous challenges, exacerbated by an aging population. Speech emerges as a ubiquitous biomarker with strong…
Enhancing Uncertainty Estimation in Neural Networks
May 6, 2025Neural networks are often overconfident about their predictions, which undermines their reliability and trustworthiness. In this presentation, I will present…
Improving Evaluation Metrics for Vision-and-Language Models
April 22, 2025Evaluating image captions is essential for ensuring both linguistic fluency and accurate semantic alignment with visual content. While reference-free metrics…