Mathematics, Год журнала: 2025, Номер 13(5), С. 850 - 850
Опубликована: Март 4, 2025
The rapid expansion of digital news sources has necessitated intelligent systems capable filtering, analyzing, and deriving meaningful insights from vast amounts information in real time. This study presents an AI-driven chatbot designed for real-time automation, integrating advanced natural language processing techniques, knowledge graphs, generative AI models to improve summarization correlation analysis. processes over 1,306,518 reports spanning 25 September 2023 17 February 2025, categorizing them into 15 primary event categories extracting key through structured By employing state-of-the-art machine learning the system enables classification, interactive query-based exploration, automated correlation. demonstrated high accuracy both tasks, achieving average F1 score 0.94 0.92 Summarization queries were processed within response time 9 s, while analyses required approximately 21 s per query. chatbot’s ability generate real-time, concise summaries uncover hidden relationships between events makes it a valuable tool applications disaster response, policy analysis, cybersecurity, public communication. research contributes field analytics by bridging gap static retrieval platforms conversational agents. Future work will focus on expanding multilingual support, enhancing misinformation detection, optimizing computational efficiency broader real-world applicability. proposed stands as scalable adaptive solution decision support dynamic environments.
Язык: Английский