This content originally appeared on DEV Community and was authored by zhangzib123
LLM-enhanced approach:
In event extraction, traditional techniques rely on rule templates and CRF models, whereas the LLM-enhanced approach employs prompt engineering and fine-tuning for intelligent semantic parsing.
Our company's Hotspot Event Analysis tool developed based on the LLM-enhanced approach has effectively met user needs in practical applications.
For contextual analysis, static knowledge graphs are upgraded to dynamic Chain-of-Thought (CoT) reasoning, enabling causal evolution tracking and real-time decision-making.
The tool extensively collects information from domestic and foreign think tanks, mainstream media, internet public sentiment, and other sources to conduct event discovery and contextual analysis, gaining real-time insights into trending events. Additionally, based on specified thematic areas (such as macroeconomic forecasting, strategies of world-class enterprises, innovation and competitiveness, etc.), it performs in-depth event mining, correlation analysis, and dynamic monitoring, automatically generating analytical reports on events.
This content originally appeared on DEV Community and was authored by zhangzib123
zhangzib123 | Sciencx (2025-07-30T10:52:39+00:00) 《Hotspot Event Analysis tool》–developed based on the LLM-enhanced approach. Retrieved from https://www.scien.cx/2025/07/30/%e3%80%8ahotspot-event-analysis-tool%e3%80%8b-developed-based-on-the-llm-enhanced-approach/
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