中圖分類號：TP391.1文獻(xiàn)標(biāo)識碼：ADOI:10.19358/j.issn.2097-1788.2023.12.004
引用格式：曾文龍,，劉丹,，張超.基于大模型的智能抄清：事件要點抽取與報告生成［J］.網(wǎng)絡(luò)安全與數(shù)據(jù)治理，2023,，42（12）：20-26.

Intelligent chaoqing based on large models: event key point extraction and report generation

Abstract： With the advent of the era of information explosion, how to efficiently extract valuable information from massive intelligence by means of chaoqing and generate accurate chaoqing reports has become an important challenge in the field of intelligence analysis and reasoning. The traditional manual chaoqing method is difficult to deal with the huge amount of data and high diversity of intelligence data, so it is necessary to use natural language technology to improve the efficiency and accuracy of chaoqing analysis. This paper proposes an intelligent chaoqing method based on a large model, which aims to extract and generate reports through event extraction. This method first uses natural language processing technology to analyze the chaoqing data, and extracts key points of document events in combination with grammatical and semantic information. Based on the generative capabilities of large models, comprehensive chaoqing reports with rich transcripts is generated.

Key words : large models; intelligent chaoqing; event key point extraction; report generation