面向非相关文献的知识关联检索系统的设计与实现

System Design and Implementation of Knowledge Correlation and Retrieval for Non-Related Documents

[目的/意义]面向非相关文献的知识关联能够促进新知识的产生,为科学研究提供了一种有效的辅助手段。[方法/过程]本文以《中国分类主题词表》为主题词受控词表,首先对文献摘要进行中文分词处理并提取主题词,利用计量分析技术和聚类技术分析文献间特征的相似、相异水平,然后基于该系统为用户检索并利用用TOP-K算法反馈用户精确结果。[结果/结论]设计了面向非相关文献的知识关联检索系统,从更细的粒度层面揭示文献之间的知识关联,为用户提供高质量的服务。

[Purpose/Meaning]Knowledge association for non-related literature can promote the generation of new knowledge and provide an effective aid for scientific research.[Methods/Processes] This paper used the“Chinese Classification Thesaurus”as the controlled word list of subject words.Firstly,the Chinese word segmentation of the document abstract was processed and the topic words were extracted.The econometric analysis technique and clustering technique were used to analyze the similarity between the documents.Different levels were then used to retrieve and utilize the TOP-K algorithm to feed back user accurate results based on the system.[Results/Conclusions]A knowledge- based retrieval system for non-related literature was designed to reveal the knowledge association between documents from a more granular level,and to provide users with high-quality services.