Aspect-based sentiment classification aims to infer the sentiment expression towards a
specific aspect in a sentence. The key to this task is to utilize the relationship between …

Despite the great manufactures' efforts to achieve customer satisfaction and improve their
performance, social media opinion mining is still on the fly a big challenge. Current opinion …

Sentiment analysis is an important area of natural language processing that can help inform
business decisions by extracting sentiment information from documents. The purpose of this …

In recent years, BERT encoder methods have been widely used in aspect term sentiment
analysis (ATSA) tasks. Many ways of putting text and aspect term into a BERT sentence …

The purpose of aspect-based sentiment classification is to identify the sentiment polarity of
each aspect in a sentence. Recently, due to the introduction of Graph Convolutional …

Aspect-level sentiment classification (ASC) is an important branch of sentiment analysis. Its
purpose is to identify the sentiment polarity of the context for a given aspect. In recent years …

Aspect-based sentiment analysis is a computationally determining opinions, sentiments, and
semantic conception of the text. Alternatively, it is a specific sentiment analysis process with …

Aspect-level sentiment analysis plays a pivotal role in fine-grained sentiment categorization,
especially given the rapid expansion of online information. Traditional methods often …

This paper describes a novel polynomial inherent attention (PIA) model that outperforms all
state‐of‐the‐art transformer models on neural machine translation (NMT) by a wide margin …

In the last decade, sentiment analysis has been a popular research area in the domains of
natural language processing and data mining. Sentiment analysis has several commercial …