基于NL2SQL的兵棋数据智能统计分析方法研究

摘要：

面对海量的兵棋数据，传统界面查询的方式已经无法满足指挥员快速、全面、精准查询数据的要求。通过深入分析兵棋数据特点与主流NL2SQL(natural language to struct query language)模型的缺陷，提出了一套适合兵棋数据智能统计查询的解决方案。针对领域数据集缺乏，提出了一套基于人机协助、动态迭代的兵棋数据集构建方案；针对兵棋查询问句时间敏感的问题，提出了一套“规则+深度学习”的时间表达式识别与规范方法；针对兵棋数据量大提取查询值困难的问题，修改完善了Bridge模型的值提取与SQL生成架构。综合运用以上方案，使兵棋数据查询的精准匹配准确率达到75%以上。

关键词:

兵棋,

NL2SQL,

数据集,

时间处理,

统计查询

Abstract:

In the face of massive wargaming data, the traditional interface query method can no longer meet the commander's requirements, i.e., fast, comprehensive, and accurate data querying. Through in-depth analysis of the characteristics of wargaming data and the defects of the mainstream natural language to struct query language (NL2SQL) model, a set of solutions for the intelligent statistical query of wargaming datais presented. Due to the lack of datasets, a wargaming dataset construction scheme based on human-machine assistance and dynamic iteration is provided. In order to solve the time-sensitive problem of wargaming querying, time expression recognition and standardization methods based on "rule + deep learning" are proposed. The value extraction and SQL generation architecture of the Bridge model are modified to facilitate the extraction of query value for a large amount of wargaming data. By comprehensively using the above scheme, the query accuracy of wargaming data is significantly enhanced to more than 75%.

Key words:

wargaming,

NL2SQL(natural language to struct query language),

dataset,

time processing,

statistical query

中图分类号:

TP31

引用本文

殷来祥,李志强,付琼莹 . 基于NL2SQL的兵棋数据智能统计分析方法研究[J]. 系统仿真学报, 2023, 35(9): 2000-2010.

Yin Laixiang,Li Zhiqiang,Fu Qiongying . Research on Intelligent Statistical Analysis of Wargaming Data Based on NL2SQL[J]. Journal of System Simulation, 2023, 35(9): 2000-2010.

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链接本文:

https://www.china-simulation.com/CN/10.16182/j.issn1004731x.joss.22-0559

https://www.china-simulation.com/CN/Y2023/V35/I9/2000