2026-10-13T22:25:15Z https://www.scidb.cn/oai

10.57760/sciencedb.j00133.00652 2026-06-29T08:54:06Z

2026-06-29 A Knowledge Graph Dataset for Research on Chinese Scientific and Technical Literature doi:10.57760/sciencedb.j00133.00652 en The proposed knowledge graph dataset for Chinese scientific and technical literature research comprises 184,078 nodes and 347,360 edges, covering multiple disciplinary domains, including computer science, medicine, agriculture, psychology, library and information science, and management science. The dataset is constructed as a literature-centered heterogeneous graph network, in which the node types include papers, authors, institutions, keywords, journals, and research fields. All entities are assigned unified identifiers to ensure consistency and facilitate downstream processing. This dataset can support a variety of research tasks, such as paper recommendation, automatic journal selection, field classification, and graph representation learning. The files in the dataset are described as follows:titleContent.csv: titles of papersabstractContent.csv: abstracts of paperskeywordContent.csv: keywords of papersfieldContent.csv: research fields of papersvenueContent.csv: journals in which the papers were publishedpa.csv: associations between papers and authorspk.csv: associations between papers and keywordspf.csv: associations between papers and research fieldspv.csv: associations between papers and publication journals Literature data; Knowledge Graph; Graph neural network; Literature Recommendation; Social network wei bin PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank