6G knowledge system construction: academic knowledge mining and on-demand application for full domains and omni scenarios

Zifan SHA; Nan CHENG; Yilong HUI; Wenwei YUE; Yuchuan FU; Ruijin SUN

doi:10.11959/j.issn.1000-436x.2023181

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6G knowledge system construction: academic knowledge mining and on-demand application for full domains and omni scenarios

Comprehensive Reviews | 更新时间：2024-06-06

- 6G knowledge system construction: academic knowledge mining and on-demand application for full domains and omni scenarios
- Journal on Communications Vol. 44, Issue 9, Pages: 173-187(2023)
- 作者机构：
  
  西安电子科技大学空天地一体化综合业务网全国重点实验室，陕西西安710071
- 作者简介：
- 基金信息：
  
  The National Key Research and Development Program of China(2020YFB1807700)
- DOI：10.11959/j.issn.1000-436x.2023181
  CLC： TN929.5
- Online First：2023-09，
  
  Published：25 September 2023
- 稿件说明：
移动端阅览
Zifan SHA, Nan CHENG, Yilong HUI, et al. 6G knowledge system construction: academic knowledge mining and on-demand application for full domains and omni scenarios[J]. Journal on Communications, 2023, 44(9): 173-187.
DOI：

Zifan SHA, Nan CHENG, Yilong HUI, et al. 6G knowledge system construction: academic knowledge mining and on-demand application for full domains and omni scenarios[J]. Journal on Communications, 2023, 44(9): 173-187. DOI： 10.11959/j.issn.1000-436x.2023181.

摘要

当前 6G 相关概念并未统一，亟待一致性的认知和定义，学术和产业界对 6G 的发展全貌和相关领域研究进展缺少清晰认识。为此，构建了 6G 知识库及知识体系。首先，对现有 6G 学术文献进行自动化筛选和结构化存储；其次，在对文本数据进行标注和规范化的基础上构建了6G知识库；再次，利用6G知识库实现了对6G全领域的统计分析；利用自然语言处理、深度神经网络和潜在树模型等技术实现对6G知识的抽取和生成。最后，在大模型训练的基础上，面向多样化的服务需求实现按需的知识应用。

Abstract

At present

the concepts related to 6G have not been unified

and there is an urgent need for consistent cognition and definition.Academics and industries lack a clear understanding of the overall development of 6G and the research progress in related fields.Therefore

the 6G knowledge base and knowledge system was constructed.Firstly

the existing 6G academic documents were automatically screened and stored in a structured way.Secondly

a 6G knowledge base was constructed on the basis of labeling and standardizing text data.In addition

a comprehensive statistical analysis was conducted across all domains of 6G based on the knowledge base and the technologies such as natural language processing

deep neural network and latent tree model were used to realize the extraction and generation of 6G knowledge.Finally

on the basis of large-scale model training

the on-demand knowledge application was realized for diversified service requirements.

关键词

Keywords

references

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