Humans are increasingly integrated with devices that enable the collection of vast
unstructured opinionated data. Accurately analysing subjective information from this data is …

Targeted sentiment classification predicts the sentiment polarity on given target mentions in
input texts. Dominant methods employ neural networks for encoding the input sentence and …

Graph convolutional networks have been successfully applied to aspect-based sentiment
analysis, due to their ability to flexibly capture syntactic information and word dependencies …

With the advancements in processing units and easy availability of cloud-based GPU
servers, many deep learning-based methods have been proposed for Aspect Level …

Educational institutions typically gather feedback from beneficiaries through formal surveys.
Offering open-ended questions allows students to express their opinions about matters that …

Recently, pre-trained language models (PLMs), especially pre-trained bidirectional encoder
representations from transformers (BERT), have improved the performance of aspect-based …

Every day millions of news articles and (micro) blogs that contain financial information are
posted online. These documents often include insightful financial aspects with associated …

Automatic short-answer grading (ASAG) is a key component of intelligent tutoring systems.
Deep learning is an advanced method to deal with recognizing textual entailment tasks in an …

In the current landscape, smartwatches have gained popularity as wearable devices thanks
to their fitness tracking and health monitoring capabilities. However, the abundance of …

Aspect-Based Sentiment Analysis (ABSA) aims to predict the sentiment polarity of different
aspects in a sentence or document, which is a fine-grained task of natural language …