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Xiao Ming: Library Journal—Research on Full-text Citation Analysis Method Based on Ontology and Linked Data

2021-05-13 Views:253

This paper proposed a full-text citation analysis method based on ontology and linked data technology, aiming to reveal the full-text citation relationship between academic literature, and to achieve a new perspective of citation analysis. First of all, we selected high-cited papers in the “citation analysis” field of the Scientometrics journal to construct experimental data sets, and extracted the full-text citation data between citing papers and cited papers. Then, a Full-text Citation Ontology (FCO) was constructed to normalize the data and publish RDF triples as citation linked data. Finally, we constructed different SPARQL queries to extract the full-text citation information in multiple dimensions. We also analyzed the citation numbers, citation functions, citation sentiments, and citation locations in detail, hoping to verify the feasibility of this method. We found that our full-text citation analysis method has certain feasibility and practicability, which is of great significance to the optimization of the traditional citation analysis method and the popularity of the full-text citation analysis method.

Shi Zeshun, Xiao Ming. Research on Full-text Citation Analysis Method Based on Ontology and Linked Data[J]. Library Journal,2021,40(04):100-108.