基于本体的任务信息需求智能解析研究

张超; 杨君刚; 卢震海; 李尧; 王连清; 蒋超

doi:10.11959/j.issn.2096-6652.ZNKX26037

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基于本体的任务信息需求智能解析研究

综述与展望 | 更新时间：2026-07-29

- 基于本体的任务信息需求智能解析研究
- Research on intelligent parsing of task information needs based on ontology
- 智能科学与技术学报 2026年8卷第2期页码：169-182
- 作者机构：
  
  1.国防科技大学研究生院，湖南长沙 410000
  2.信息支援部队工程大学，湖北武汉 430000
- 作者简介：
  
  张超（1988- ），男，国防科技大学研究生院博士生，主要研究方向为本体工程、智能信息服务。
  杨君刚（1973- ），男，博士，信息支援部队工程大学教授、博士生导师，主要研究方向为人工智能、信息服务、光通信。yangjungang17@nudt.edu.cn
  卢震海（2000- ），男，国防科技大学研究生院博士生，主要研究方向为本体理论与工程。
  李尧（1992- ），男，国防科技大学研究生院硕士生，主要研究方向为信息通信。
  王连清（1985- ），男，信息支援部队工程大学副教授，主要研究方向为人工智能、智能视觉。
  蒋超（1994- ），男，信息支援部队工程大学讲师，主要研究方向为方程发现。
- 基金信息：
  
  国家自然科学基金项目(62402505);国防科技大学自主创新科学基金(22-ZZCX-055)
- DOI：10.11959/j.issn.2096-6652.ZNKX26037
  中图分类号： TP39
- 收稿：2026-03-20，
  
  修回：2026-05-03，
  
  录用：2026-05-18，
  
  网络首发：2026-07-27，
  
  纸质出版：2026-06-15
- 稿件说明：
移动端阅览
张超,杨君刚,卢震海等.基于本体的任务信息需求智能解析研究[J].智能科学与技术学报,2026,08(02):169-182.

Zhang Chao,Yang Jungang,Lu Zhenhai,et al.Research on intelligent parsing of task information needs based on ontology[J].Chinese Journal of Intelligent Science and Technology,2026,08(02):169-182.
张超,杨君刚,卢震海等.基于本体的任务信息需求智能解析研究[J].智能科学与技术学报,2026,08(02):169-182. DOI： 10.11959/j.issn.2096-6652.ZNKX26037.

Zhang Chao,Yang Jungang,Lu Zhenhai,et al.Research on intelligent parsing of task information needs based on ontology[J].Chinese Journal of Intelligent Science and Technology,2026,08(02):169-182. DOI： 10.11959/j.issn.2096-6652.ZNKX26037.

摘要

针对时间敏感性任务场景中信息需求解析面临的挑战，提出一种基于本体的智能解析方法。首先通过设计本体模型对任务与力量进行形式化描述；其次建立以本体模型为基础的语义转换与逻辑推理方法，实现从非结构化任务描述到结构化信息需求清单的自动生成。实验结果表明，该方法能够生成规范翔实的信息需求清单，与传统人工分析的方式相比，信息保障的效率得到显著提升。

Abstract

To address the challenges faced in the analysis of information needs in time-sensitive task scenarios

an intelligent parsing method based on ontology was proposed. Firstly

an ontology model was designed to describe tasks and forces formally. Secondly

a semantic transformation and logical reasoning method based on the ontology model was established to automatically generate a structured list of information needs from unstructured task descriptions. The experimental results show that this method can generate a standardized and detailed list of information needs. Compared with traditional manual analysis

the efficiency of information assurance is significantly improved.

关键词

Keywords

references

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