context aware news classification

This research on context-aware news classification leveraging semantic understanding aims to enhance the accuracy and relevance of news categorization by incorporating contextual and semantic features. By utilizing natural language processing (NLP), deep learning, and contextual embeddings, this study seeks to go beyond traditional keyword-based classification, capturing nuanced meanings and relationships between words. This approach improves the model's ability to understand the intent, tone, and deeper context of news articles, leading to more precise and contextually aware classifications. The work contributes to the development of intelligent news recommendation systems and improved misinformation detection