Deep learning has emerged as a powerful machine learning technique that learns multiple
layers of representations or features of the data and produces state‐of‐the‐art prediction …

The domain of Aspect-based Sentiment Analysis, in which aspects are extracted, their
sentiments are analysed and sentiments are evolved over time, is getting much attention …

As an important fine-grained sentiment analysis problem, aspect-based sentiment analysis
(ABSA), aiming to analyze and understand people's opinions at the aspect level, has been …

Due to their inherent capability in semantic alignment of aspects and their context words,
attention mechanism and Convolutional Neural Networks (CNNs) are widely applied for …

In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …

Aspect Sentiment Triplet Extraction (ASTE) is the task of extracting the triplets of target
entities, their associated sentiment, and opinion spans explaining the reason for the …

Aspect-based sentiment classification is a popular task aimed at identifying the
corresponding emotion of a specific aspect. One sentence may contain various sentiments …

In this paper, we investigate the modeling power of contextualized embeddings from pre-
trained language models, eg BERT, on the E2E-ABSA task. Specifically, we build a series of …

We propose a novel multi-grained attention network (MGAN) model for aspect level
sentiment classification. Existing approaches mostly adopt coarse-grained attention …

Target-oriented sentiment classification aims at classifying sentiment polarities over
individual opinion targets in a sentence. RNN with attention seems a good fit for the …