Pavitar Parkash Singh
Biographic Data
| ID | 9623634 |
|---|---|
| NAME | Pavitar Parkash Singh |
| GIVEN NAMES | Pavitar Parkash |
| FAMILY NAME | Singh |
| SIGNATURE | SINGH P P |
| AFFILIATIONS | Lovely Professional University |
| ORCID | 0000-0001-9334-1952 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| 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. …
Public perception of crisis in companies
Crisis is inevitable and in today’s scenario with the pandemic affecting every aspect of our lives, crisis has become something which every industry has had to deal with. The more important aspect today is, how to deal with crisis today. To do so it becomes necessary to understand and evaluate the impact it has on the brand. The study focuses on the impact of crisis on brand image and reputation. The study was conducted amongst the people of Jala…
No prominent works on this page.
Public perception of crisis in companies
Crisis is inevitable and in today’s scenario with the pandemic affecting every aspect of our lives, crisis has become something which every industry has had to deal with. The more important aspect today is, how to deal with crisis today. To do so it becomes necessary to understand and evaluate the impact it has on the brand. The study focuses on the impact of crisis on brand image and reputation. The study was conducted amongst the people of Jala…
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) · Advertising (1 work) · Artificial Intelligence (1 work) · Business (1 work) · Computer Science (1 work) · COVID-19 Pandemic Impacts (1 work) · Crisis communication (1 work) · Crisis management (1 work) · Data science (1 work) · Deep learning (1 work)