Knowledge Management and Intelligent Applications of Engineering Archives Based on NLP Technology
TANG Huiqing
BI Baoli
LU Xiaotong
Abstract：Addressing issues such as the low efficiency of knowledge reuse in the surveying and design industry and the lack of intelligent design tools,a framework for archival knowledge mining and intelligent services integrating Natural Language Processing(NLP)technology was proposed.By constructing a"1+N+X"archival data resource system and proposing a"6-in-1"data governance strategy,a multi-dimensional archival analysis and evaluation model was established to select high-quality archival resources and deconstruct knowledge.Combining the ERNIE pre-training model with machine learning algorithms,semantic analysis and knowledge-based recommendation of archives were achieved.Starting from business scenarios,design tools deeply integrated into the core design platform were developed to facilitate data integration,sharing,and common use across platforms.This enabled the intelligent generation of long engineering design reports and promoted a paradigm shift in archival services from"passive querying"to"active empowerment,"thereby forming a closed-loop knowledge flow of"mining-application-regeneration."The results provide solutions and demonstrations for the deep value mining and intelligent application of archival resources.
Keywords：engineering archiveengineering design reportautomatic document generationknowledge managementdata governancearchival data classification and gradingNLP
Publication Date：2025-12-20
Online Publishing Date：2026-03-04(First online date of this platform, not the publication date of the document)
Pages：7( 61-67 )