基于语义特征挖掘的图书馆文献资源智能检索方法

Intelligent Retrieval Method for Library Literature Resources Based on Semantic Feature Mining

为提升图书馆文献资源检索精度,使检索结果与索引标准、用户需求适配,文章提出基于语义特征挖掘的图书馆文献资源智能检索方法。构建图书馆元数据特征空间,计算特征空间量化结果与特征信息的聚类范围;对图书馆文献资源信息进行编码重构与分布采集,提取图书馆文献资源检索特征;计算特征相似度分数,提取显性关键词;利用加权向量组合控制方法优化图书馆文献检索,实现文献资源智能检索输出。实验结果表明,利用所提方法获取的检索结果,适配度均在98%以上,最高检索精度达到0.97,有较好实际应用效果。

In order to improve the accuracy of library literature resource retrieval and make the retrieval results compatible with index standards and user needs,this paper proposes an intelligent retrieval method for library literature resources based on semantic feature mining.By constructing the metadata feature space of the library,the quantification results of the feature space and the clustering range of feature information are calculated;encoding reconstruction and distribution collection of library literature resource information,extracting retrieval features of library literature resources;calculate feature similarity scores and extract explicit keywords;using weighted vector combination control method to optimize library literature retrieval and achieve intelligent retrieval output of literature resources.The experimental results show that the retrieval results obtained using the proposed method have an adaptation rate of over 98%,and the highest retrieval accuracy reaches 0.97,indicating good practical application effects.