Latika Jindal
Biographic Data
| ID | 10056384 |
|---|---|
| NAME | Latika Jindal |
| GIVEN NAMES | Latika |
| FAMILY NAME | Jindal |
| SIGNATURE | JINDAL L |
| AFFILIATIONS | Medi-Caps University |
| ORCID | 0009-0007-8484-1219 |
| VERIFIED | Yes |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Deep Learning Model for Interpretability and Explainability of Aspect-Level Sentiment Analysis Based on Social Media
The interactive attention graph convolution network (IAGCN), a novel model proposed in this article, will revolutionize aspect-level sentiment analysis (SA). IAGCN effectively addresses these key features, in contrast to prior research that ignored the meaning of aspect terms and their relationship with context. The model combines a modified dynamic weighting layer with bidirectional long short-term memory (BiLSTM) to accurately acquire context. …
No prominent works on this page.
Deep Learning Model for Interpretability and Explainability of Aspect-Level Sentiment Analysis Based on Social Media
The interactive attention graph convolution network (IAGCN), a novel model proposed in this article, will revolutionize aspect-level sentiment analysis (SA). IAGCN effectively addresses these key features, in contrast to prior research that ignored the meaning of aspect terms and their relationship with context. The model combines a modified dynamic weighting layer with bidirectional long short-term memory (BiLSTM) to accurately acquire context. …
Advanced Text Analysis Techniques (1 work) · Artificial Intelligence (1 work) · Computer Science (1 work) · Data science (1 work) · Deep learning (1 work) · Interpretability (1 work) · Machine learning (1 work) · Natural language processing (1 work) · Sentiment analysis (1 work) · Sentiment Analysis and Opinion Mining (1 work)