Sentence-level sentiment analysis based on supervised gradual machine learning. [PDF]
Sci Rep, 2023 Su J +5 more
europepmc +1 more source
A semantically enhanced dual encoder for aspect sentiment triplet extraction [PDF]
, 2023 Baoxing Jiang +4 more
openalex +1 more source
Deep learning for aspect-based sentiment analysis: a review. [PDF]
PeerJ Comput Sci, 2022 Zhu L, Xu M, Bao Y, Xu Y, Kong X.
europepmc +1 more source
Making Better Use of Training Corpus: Retrieval-based Aspect Sentiment Triplet Extraction via Label Interpolation [PDF]
, 2023 Guoxin Yu +4 more
openalex +1 more source
Deep Content Understanding Toward Entity and Aspect Target Sentiment Analysis on Foundation Models
Introducing Entity-Aspect Sentiment Triplet Extraction (EASTE), a novel Aspect-Based Sentiment Analysis (ABSA) task which extends Target-Aspect-Sentiment Detection (TASD) by separating aspect categories (e.g., food#quality) into pre-defined entities (e.g.
Basic, Milos +2 more
core
Attention-Enabled Ensemble Deep Learning Models and Their Validation for Depression Detection: A Domain Adoption Paradigm. [PDF]
Diagnostics (Basel), 2023 Singh J +4 more
europepmc +1 more source
Test-Time Code-Switching for Cross-lingual Aspect Sentiment Triplet Extraction [PDF]
Dongming Sheng +6 more
openalex +3 more sources
Deep learning based sentiment analysis and offensive language identification on multilingual code-mixed data. [PDF]
Sci Rep, 2022 Shanmugavadivel K +5 more
europepmc +1 more source
Dynamic Invariant-Specific Representation Fusion Network for Multimodal Sentiment Analysis. [PDF]
Comput Intell Neurosci, 2022 He J, Yanga H, Zhang C, Chen H, Xua Y.
europepmc +1 more source
Rethinking ASTE: A Minimalist Tagging Scheme Alongside Contrastive Learning
Aspect Sentiment Triplet Extraction (ASTE) is a burgeoning subtask of fine-grained sentiment analysis, aiming to extract structured sentiment triplets from unstructured textual data.
Gu, Qinying +4 more
core