基于本体论的数字图书馆信息检索技术

Information Retrieval Technology of Digital Library Based on Ontology

为进一步提高用户信息检索的准确性和效率,在研究了基于信息检索和领域本体知识库的用户检索模型基础上,本文设计了一种智能图书馆管理系统。此外,引入遗传算法训练调整选项加权因子,从而提高系统查全率和查准率。通过仿真分析,本文方法与模拟退火法模型进行对比,泛化能力更强,预测平均距离更低。仿真结果进一步验证了本文方法的有效性及实用性。

In order to further improve the accuracy and efficiency of user information retrieval,based on the research of user retrieval model based on information retrieval and domain ontology knowledge base,this paper designs an intelligent library management system.In addition,genetic algorithm is introduced to train and adjust the option weighting factor,so as to improve the recall and precision of the system.Through simulation analysis,compared with the simulated annealing model,the proposed method has stronger generalization ability and lower average prediction distance.The simulation results further verify the effectiveness and practicability of the proposed method.