摘要
针对目前部分数字图书馆信息检索系统性能及检索效率较低的现状,构建了一种整体检索性能更优的图书馆信息检索系统模型。该模型是基于人工智能技术,在引入贝叶斯理论的基础上,结合随机森林算法构建的数字图书馆信息检索系统模型。对比现有的检索系统模型,该模型可以获得更高的检索精度、查准率、查全率,并进一步缩短了检索时间,其检索性能已经在数字图书馆信息检索系统中得到了验证。
To address the current low performance and efficiency of some digital library information retrieval systems,a library information retrieval system model with better overall retrieval performance is constructed.This model is a digital library information retrieval system model based on artificial intelligence technology,which combines Bayesian theory and random forest algorithm.Compared with the existing retrieval system models,this model can achieve higher retrieval accuracy,precision ratio,recall ratio,and further shorten retrieval time.The efficiency of its retrieval performance has been verified in digital library information retrieval systems.
作者
陈天宇
CHEN Tian-yu(School of Beijing Institute of Graphic Communication,Beijing 102600,China)
出处
《信息技术》
2024年第7期173-179,共7页
Information Technology
关键词
人工智能
数字图书馆
信息检索
贝叶斯网络
随机森林
artificial intelligence
digital library
information retrieval
Bayesian network
random forest
