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面向非相关文献的知识关联检索系统的设计与实现
引用本文:刘爱琴,安婷.面向非相关文献的知识关联检索系统的设计与实现[J].现代情报,2019,39(8):52-58.
作者姓名:刘爱琴  安婷
作者单位:山西大学经济与管理学院, 山西 太原 030006
基金项目:山西大学人文社会科学科研基金项目"基于跨界思维的信息咨询新业态研究"(项目编号:115546003)。
摘    要: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。

关 键 词:非相关文献  知识关联  中国分类主题词表  计量分析技术  知识发现

System Design and Implementation of Knowledge Correlation and Retrieval for Non-Related Documents
Authors:Liu Aiqin  An Ting
Institution:School of Economics and Management, Shanxi University, Taiyuan 030006, China
Abstract: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.
Keywords:on-related literature  knowledge relevance  China Classification Thesaurus Table  metrological analysis technique  knowledge retrieval  
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