摘要
传统检索工具内部模型存在缺陷,改变搜索阈值会导致检索的查全率和查准率降低,因此设计基于向量空间模型的信息资源关键词智能检索工具。创建优化循环架构,优化处理关键词;计算优化后关键词与未知文档间的夹角,得到信息关键词,转换成特征向量矩阵形式,以空间向量模型为参照,完成检索时相关指标的关联匹配;根据检索工具的特点设计智能检索分布,完善模型转换过程,实现信息资源关键词智能检索工具的设计。实验测试结果显示:所设计检索工具可有效智能检索关键词,在搜索阈值增大时,其F值能保证在70%以上,检索性能更加稳定。
There are some defects in the internal model of traditional retrieval tools.Changing the search threshold will reduce the recall and precision of retrieval.Therefore,an intelligent retrieval tool for information resources keywords based on vector space model is designed.It creates optimization cycle architecture,optimizes the processing of keywords;The included angle between the optimized keywords and the unknown documents is calculated to obtain the information keywords,which are converted into the form of eigenvector matrix,and then the correlation matching of relevant indexes is completed with the spatial vector model as the reference.The intelligent retrieval distribution is designed according to the characteristics of the retrieval tools,and the model transformation process is improved to realize the design of the intelligent retrieval tools for keywords in information resources.The experimental test results show that the designed retrieval tool can effectively and intelligently retrieve keywords.When the search threshold increases,its F value can be guaranteed to be above 70%,and the retrieval performance is more stable.
作者
刘宁
牛佳乐
郑剑
李思岑
王丹丹
LIU Ning;NIU Jia-le;ZHENG Jian;LI Si-cen;WANG Dan-dan(State Grid Tianjin Electric Power Company,Tianjin 300001 China;Tianjin Sanyuan Electric Information Technology Co.,Ltd.,Tianjin 300010 China)
出处
《自动化技术与应用》
2023年第10期105-107,161,共4页
Techniques of Automation and Applications
关键词
向量空间模型
信息资源
关键词智能检索
vector space model
information resources
key words intelligent retrieval
