情报科学 ›› 2024, Vol. 42 ›› Issue (5): 35-47.

• 理论研究 • 上一篇    下一篇

总体国家安全观下的南海维权档案系统构建研究

  

  • 出版日期:2024-05-05 发布日期:2024-07-26

  • Online:2024-05-05 Published:2024-07-26

摘要:

【目的/意义】为了维护南海领土主权权益和领土完整,同时为科研人员或相关部门提供充足的南海维权档
案资料,辅助他们的科研工作,提高科研效率。【方法/过程】本文首先通过CiteSpace详细论述目前国内外南海档案
及南海档案系统研究现状;其次,运用文献调研法,整理多源异构的南海档案资料,由于工作量艰巨,本文最终从南
海文库数字资源中随机抽取302篇南海档案资料作为本文的数据基础;再次,应用正则表达式从多模态南海档案资
料中抽取具体的一句话作为细粒度南海档案数据;为了进一步提取细粒度南海维权档案数据,通过人工标注2272
条有价值和没有价值的细粒度南海档案数据,应用机器学习和深度学习算法对细粒度南海档案数据进行抽取及比
较;最后应用知识图谱构建南海维权档案系统,实现细粒度南海档案数据的检索及可视化。【结果/结论】本文最终
选择DNN模型抽取细粒度南海档案数据,其准确率达0.86。本研究具有一定的可行性,可以为后续的研究者抛砖
引玉。【创新/局限】面向总体国家安全观构建南海维权档案系统,初步实现细粒度南海维权档案数据检索及可
视化。

Abstract:

【Purpose/significance】In order to safeguard territorial sovereignty and integrity in the South China Sea and provide ample
archives and information on South China Sea rights protection for researchers and relevant institutions, thus assisting them in their sci⁃
entific research work and improving research efficiency.【Method/process】This article first provides a detailed exposition of the cur⁃
rent research status of South China Sea archives and South China Sea archive systems both domestically and internationally using
CiteSpace. Secondly, through literature research, it organizes diverse and heterogeneous South China Sea archival materials. Due to
the enormous workload, this article randomly selects 302 South China Sea archival materials from the digital resources of the South
China Sea Library as the data foundation. Thirdly, by applying regular expressions, it extracts specific sentences as fine-grained South
China Sea archival data from multi-modal South China Sea archival materials. In order to further extract fine-grained South China Sea
rights protection archival data, 2272 valuable and non-valuable fine-grained South China Sea archival data are manually annotated,
and machine learning and deep learning algorithms are applied to extract and compare the fine-grained South China Sea archival data.
Finally, a knowledge graph is applied to construct the South China Sea rights protection archives system, enabling the retrieval and vi⁃
sualization of fine-grained South China Sea archival data.【Result/conclusion】In the end, this article selects the DNN model to extract
fine-grained South China Sea archival data, achieving an accuracy of 0.86. This research demonstrates a certain feasibility and can
serve as a starting point for future researchers
.
【Innovation/limitation】Build the South China Sea Rights Protection Archives System fo⁃
cusing on the overall national security concept, and preliminarily realize the fine-grained retrieval and visualization of the South China
Sea Rights Protection Archives data.