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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (4): 57-66    DOI: 10.11925/infotech.2096-3467.2017.04.07
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Identifying Semantic Relations of Clusters Based on Linked Data
Cui Jiawang1,2(), Li Chunwang1
1National Science Library, Chinese Academy of Sciences, Beijing 100190, China
2University of Chinese Academy of Sciences, Beijing 100049, China
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[Objective] This paper introduces a model to identify the semantic relations for the co-word analysis results based on linked data. [Methods] First, we used Google Scholar, Springer and CNKI to retrieve the literature of the related research. Then, we analyzed the clusters relations of them. Finally, we constructed and examined the semantic relation model for clusters based on the linked data graph structure. [Results] The linked data helped us effectively explore the potential semantic relations among keywords. [Limitations] Due to the limits of the collected linked data, we only identified some sematic relationship, such as hierarchical, simple relavent, as well as classes-instance ones. More research is needed to improve the quality of linked data. [Conclusions] The proposed model could successfully discover the semantic relations among keywords, which help us get more insights from the cluster analysis.

Key wordsLinked Data      Co-word Cluster Analysis      Cluster      Semantic Relations Revealing Model     
Received: 16 February 2017      Published: 24 May 2017
ZTFLH:  G25  

Cite this article:

Cui Jiawang,Li Chunwang. Identifying Semantic Relations of Clusters Based on Linked Data. Data Analysis and Knowledge Discovery, 2017, 1(4): 57-66.

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关联路径 重要性指标 类型
$\{<\text{Cloning}>\xrightarrow{\text{http://dbpedia}\text{.org/ontology/wikiPageWikiLink}}\text{PCR }\!\!\}\!\!\text{ }$ 0.001 DR
$\{<\text{Cloning}>\xrightarrow{\text{wikiPageWikiLink}}$<Cloning_vector >$\xrightarrow{\text{wikiPageWikiLink}}$<PCR>} 0.00000072 IR
$\{<\text{Cloning}>\xrightarrow{\text{wikiPageWikiLink}}$<Bisulfite_sequencing >$\xrightarrow{\text{wikiPageWikiLink}}$<PCR>}
$\{<\text{Cloning}>\xrightarrow{\text{http://www}\text{.w3}\text{.org/2004/02/skos/core }\!\!\#\!\!\text{ broader}}<\text{Category:Cloning}>$
$\xrightarrow{\text{http://www}\text{.w3}\text{.org/2004/02/skos/core }\!\!\#\!\!\text{ broader}}<\text{Category:Biotechnology}>$
0.00000072 IR
$\xleftarrow{\text{http://purlorg/dc/terms/subject}}<\text{PCR}>\}$ 0.00118999 LCAR
$\{<\text{Cloning}>\xrightarrow{\text{wikiPageWikiLink}}$< Molecular_cloning>$\xrightarrow{\text{http://purlorg/dc/terms/subject}}$
0.000260651 LCAR
$\{<\text{Cloning}>\xleftarrow{\text{http://purlorg/dc/terms/subject}}<\text{Category:}\ \text{Molecular }\!\!\_\!\!\text{ biology}>$
0.00720822 LCDR
$\{<\text{Cloning}>\xleftarrow{\text{rdf:type}}<\text{http://dbpedia}\text{.org/dbtax/Technique}>\xrightarrow{\text{rdf:type}}$<PCR>} 0.00139680 LCDR
序号 属性 出现频次 含义 语义关系
1 172 300 574 对应Wikipedia的链接信息 相关关系
2 66 418 990 资源的标签信息 类和实例关系
3 40 637 907 指向同义资源 等同关系
4 36 772 939 RDF抽取所用模版信息 相关关系
5 23 809 294 Wikipedia超链接的文本信息 相关关系
6 22 673 220 资源的主题信息 类和实例关系
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