MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202641043220 A) filed by M Yogadharani; K. Prema; Selvendran Ganesan; Elavarasi T; Mr. Adhiseshan N; Dr. G. Ganesh Kumar; Mrs. Janani T; Yazhini R; Ms. K. Deepa; and G. Priyanga, Coimbatore, Tamil Nadu, on April 4, for 'system and method for sentiment classification using deep learning techniques.'
Inventor(s) include M Yogadharani; K. Prema; Selvendran Ganesan; Elavarasi T; Mr. Adhiseshan N; Dr. G. Ganesh Kumar; Mrs. Janani T; Yazhini R; Ms. K. Deepa; and G. Priyanga.
The application for the patent was published on April 17, under issue no. 16/2026.
According to the abstract released by the Intellectual Property India: "The invention discloses a system and method for sentiment classification using deep learning techniques. The system comprises a data preprocessing module, a hybrid neural network architecture, an attention-based sentiment classifier, and a visualization dashboard. Textual input is normalized, tokenized, and embedded before being processed by convolutional and recurrent layers that extract features and model sequences. Attention mechanisms highlight sentiment-relevant tokens, and the classifier outputs probability scores for each sentiment class. The dashboard visualizes sentiment trends, keyword highlights, and classification metrics, supporting real-time updates and external API integration. The system is trained on large-scale annotated datasets and fine-tuned for specific domains using transfer learning. It supports incremental learning and emphasizes interpretability through attention weights and visual explanations. Benchmark results show improved accuracy and reduced false positives compared to baseline models. The invention addresses limitations of prior art by combining multiple deep learning components into a unified sentiment analysis pipeline, offering scalability, transparency, and adaptability across industries."
Disclaimer: Curated by HT Syndication.
