摘要
本文主要通过构建弱人工智能模型,研究企业档案数据的深度利用。针对档案数据保密要求高、价值密度大的特点,基于档案数据基础构建语言类预判模型,对可能的数据利用方向进行穷举学习,通过学习迭代模型,达到弱人工智能辅助企业档案利用的目的,为档案价值挖掘提供更为有效的手段,为企业档案数据融入通用大型信息模型试错和积累经验。
This article mainly focuses on the in-depth utilization of enterprise archival data by constructing a weak artificial intelligence model.Considering the high confidentiality requirements and high value density of archival data,a language-based prediction model is built based on the archival data foundation.Through exhaustive learning of potential data utilization directions and iterative learning of the model,the purpose of weak artificial intelligence assisting enterprise archival utilization is achieved.This provides a more effective means for mining the value of archives and provides trial and error and accumulated experience for integrating enterprise archival data into general large-scale information models.
作者
范海斌
Haibin Fan(Guoneng Shendong Coal Group Corporation,Yulin,Shaanxi 791315,China)
出处
《产业科技创新》
2024年第3期93-96,共4页
Industrial Technology Innovation
关键词
人工智能
企业大数据
artificial intelligence
enterprise big data
