[Purpose/significance] To solve the general problems in co-word analysis, we propose a method for constructing and analyzing fine-grained semantic co-word network. [Method/process] The standard concepts and semantic relations between concepts were extracted from the source text with SemRep and hence the semantic co-word network was built. The feature words were extracted according to the centrality of the nodes and the frequency of the edges. The semantic predications were grouped based on the semantic schema defined by UMLS semantic network and the mapping from concept to its semantic type and semantic type to semantic type group. [Result/conclusion] Compared with routine co-word analysis method, the fine-grained semantic co-word analysis we proposed can effectively represent the content for source text. UMLS semantic network can be used to partition the semantic co-word network accurately.
Zhang Han
,
Zhao Yuhong
. Construction of Semantic Co-word Knowledge Network for Medical Literature: Method and Empirical Study[J]. Library and Information Service, 2016
, 60(11)
: 135
-142
.
DOI: 10.13266/j.issn.0252-3116.2016.11.019
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