[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.
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