基于引用关系和聚类分析的文献检索优化研究

Research on Optimization of Literature Retrieval Based on Reference Relationships and Cluster Analysis

随着数字图书馆的快速发展,如何优化文献检索方法、提高用户体验成为一个重要的问题。传统检索方法有其自身的优势并处在不断的发展中,却忽略了引用关系中蕴含的文献间相关性。在调研已有相关文献的基础上,引入一种文献结构模型,并在传统检索结果的基础上,利用文献间的直接或间接引用关系对结果文献库进行聚类,并对结果进行可视化,从而帮助用户对检索结果组成有清晰的认识,快速找到目标文献。

With the rapid development of digital libraries,how to optimize literature retrieval methods and improve users’ experiences has become an important issue.The traditional retrieval methods have their own advantages and are in continuous development,but neglect the correlation between literatures contained in reference relationships.Based on the survey of the relevant literatures,this article introduces a structural model of literature,and based on the traditional retrieval results,uses the direct or indirect reference relationships between literatures to cluster the resultant literature bases.Furthermore,the results are visualized to help users have a clear understanding of the composition of the retrieval results so as to quickly find the target literatures.