Article ; Online: Graph-based methods for Author Name Disambiguation: a survey.
PeerJ. Computer science
2023 Volume 9, Page(s) e1536
Abstract: Scholarly knowledge graphs (SKG) are knowledge graphs representing research-related information, powering discovery and statistics about research impact and trends. Author name disambiguation (AND) is required to produce high-quality SKGs, as a ... ...
Abstract | Scholarly knowledge graphs (SKG) are knowledge graphs representing research-related information, powering discovery and statistics about research impact and trends. Author name disambiguation (AND) is required to produce high-quality SKGs, as a disambiguated set of authors is fundamental to ensure a coherent view of researchers' activity. Various issues, such as homonymy, scarcity of contextual information, and cardinality of the SKG, make simple name string matching insufficient or computationally complex. Many AND deep learning methods have been developed, and interesting surveys exist in the literature, comparing the approaches in terms of techniques, complexity, performance, |
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Language | English |
Publishing date | 2023-09-11 |
Publishing country | United States |
Document type | Journal Article |
ISSN | 2376-5992 |
ISSN (online) | 2376-5992 |
DOI | 10.7717/peerj-cs.1536 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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