Summarizing News Text with Multi-Feature Analysis and Fuzzy Logic

This study presents a novel news summary technique that creates succinct and educational summaries by utilizing fuzzy logic and multi-feature analysis. To precisely assess sentence significance, the model uses fuzzy rules to extract key sentences based on their position, phrase frequency, and content structure. Readers will be certain to receive thorough information in a timely and effective manner because of this innovative technique. The summarizing model's capacity to generate high-quality summaries is improved by combining fuzzy logic with multi-feature extraction, which makes it ideal for real-time news applications and media contexts with an extensive amount of information.