Sentence-Level Aspect-Based Sentiment Analysis for Classifying Adverse Drug Reactions (ADRs) Using Hybrid Ontology-XLNet Transfer Learning

Sentence-Level Aspect-Based Sentiment Analysis for Classifying Adverse Drug Reactions (ADRs) Using Hybrid Ontology-XLNet Transfer Learning

This paper presents a hybrid ontology-XLNet sentiment analysis classification approach for sentence-level aspects. The main objective of the proposed approach allows discovering user social data considering the extracted in-depth inference about sentiment depending on the context. Thus, in this pape...

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Bibliographic Details
Main Authors: Asmaa Hashem Sweidan, Nashwa El-Bendary, Haytham Al-Feel
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Aspect
sentiment analysis
adverse drug reactions (ADRs)
XLNet
ontology
transfer learning
Online Access:https://ieeexplore.ieee.org/document/9461832/

Internet

https://ieeexplore.ieee.org/document/9461832/

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