摘要
针对共词分析方法存在的词对共现统计粒度过粗、共词分析结果解释不一致等问题,本文提出一种细粒度语义共词分析方法。该方法一方面对词对共现统计单元进行碎片化,由“文献单元”变为“知识单元”(RDF三元组),达到细粒度的目的;另一方面对共词分析方法进行语义化,将共现词对的语义信息融入到共词分析过程之中。最后,本文借助该方法进行了实证研究,并在一定程度上验证了该方法的科学性和有效性。
in view of the problems of indexes and the cognitive problems concerning interpretation in co-word analysis, this paper proposed a fine-grained semantic co-word analysis method. In order to realize the fine-grained semantic co-word analysis, on the one hand, the statistic unit of the co-words is changed from "articles unit" to "knowledge (RDF) unit"; on the other hand, semantic of co-word is integrate into the method. At last, this paper analyzed the soundness of the proposed method through experiment in the research field of linked data.
出处
《情报学报》
CSSCI
北大核心
2014年第9期969-978,共10页
Journal of the China Society for Scientific and Technical Information
基金
国家社会科学基金项目“基于关联数据的数字图书馆多粒度集成知识服务研究”(批准号:14CTQ003)
关键词
共词分析
语义
细粒度
关联数据
co-word analysis, semantic, granularity, linked data