Sentiment analysis is the task of detecting opinions of people from text using techniques of natural language processing. It is critical in assisting businesses in actively improving their …
Z Feng, H Zhou, Z Zhu, K Mao - Expert Systems with Applications, 2022 - Elsevier
In synonym replacement-based data augmentation techniques for natural language processing tasks, words in a sentence are often sampled randomly with equal probability. In …
With the expansion of social networks, sentiment analysis has become one of the hot topics in machine learning. However, in traditional sentiment analysis, the text is considered of a …
SD Gogula, M Rahouti, SK Gogula, A Jalamuri… - Applied Sciences, 2023 - mdpi.com
Sentiment analysis (SA), and emotion detection and recognition from text (EDRT) are recent areas of study that are closely related to each other. Sentiment analysis strives to identify …
S Rani, A Jain - Multimedia Tools and Applications, 2024 - Springer
User-generated content on healthcare web forums, particularly drug reviews, provides valuable information on drug benefits, effectiveness, side effects, dosage, condition, cost …
Ontologies are widely used for representing domain knowledge and meta data, playing an increasingly important role in Information Systems, the Semantic Web, Bioinformatics and …
G Dubey, HP Singh, K Sheoran… - Concurrency and …, 2023 - Wiley Online Library
In drug review sentimental analysis (SA), users can share their experiences after consuming the drugs, which provides an accurate decision about the safety of the drug and public …
H Huan, Z He, Y Xie, Z Guo - IEEE Access, 2022 - ieeexplore.ieee.org
Aspect Sentiment Triplet Extraction (ASTE) is a complex and important task in aspect-based sentiment analysis task, which aims to extract aspect-sentiment-opinion triplets from review …
D Wu, Z Wang, W Zhao - Multimedia Tools and Applications, 2024 - Springer
Aiming at the problem that the feature information of review text is not fully captured and the aspect information extraction ability is poor in the traditional aspect-level sentiment …