Aspect Term Extraction and Sentiment Classification
6 papers with code • 1 benchmarks • 3 datasets
Extracting the aspect terms as well as the corresponding sentiment polarities simultaneously.
Aspect-based sentiment analysis produces a list of aspect terms and their corresponding sentiments for a natural language sentence.
Aspect-based Sentiment Analysis (ABSA) aims to identify the aspect terms, their corresponding sentiment polarities, and the opinion terms.
Open-domain targeted sentiment analysis aims to detect opinion targets along with their sentiment polarities from a sentence.
Aspect-based sentiment analysis (ABSA) involves three subtasks, i. e., aspect term extraction, opinion term extraction, and aspect-level sentiment classification.
One of the remaining challenges for aspect term extraction in sentiment analysis resides in the extraction of phrase-level aspect terms, which is non-trivial to determine the boundaries of such terms.
In this work, we argue that two kinds of gaps, i. e., domain gap and objective gap, hinder the transfer of knowledge from pre-training language models (PLMs) to ABSA tasks.