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Graph-based methods for Author Name Disambiguation: a survey [PDF]
PeerJ Computer Science, 2023 Scholarly knowledge graphs (SKG) are knowledge graphs representing research-related information, powering discovery and statistics about research impact and trends.
Michele De Bonis +2 more
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Author name disambiguation based on heterogeneous graph neural network. [PDF]
PLoS ONEWith the dramatic increase in the number of published papers and the continuous progress of deep learning technology, the research on name disambiguation is at a historic peak, the number of paper authors is increasing every year, and the situation of ...
Ge Wang +3 more
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A Graph-Based Author Name Disambiguation Method and Analysis via Information Theory [PDF]
Entropy, 2020 Name ambiguity, due to the fact that many people share an identical name, often deteriorates the performance of information integration, document retrieval and web search.
Youlong Wu, Yingying Ma, Chengqiang Lu
exaly +4 more sources
Aggregating large-scale databases for PubMed author name disambiguation. [PDF]
Journal of the American Medical Informatics Association: JAMIA, 2021 OBJECTIVE PubMed has suffered from the author ambiguity problem for many years. Existing studies on author name disambiguation (AND) for PubMed only used internal metadata for development. However, some of them are incomplete (eg, a large number of names
Yong Huang, Wei Lu
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Dual-Channel Heterogeneous Graph Network for Author Name Disambiguation
Information (Switzerland), 2021 Name disambiguation has long been a significant issue in many fields, such as literature management and social analysis. In recent years, methods based on graph networks have performed well in name disambiguation, but these works have rarely used ...
Yong Zhang, Pengyu Zhang
exaly +4 more sources
Name Disambiguation Scheme Based on Heterogeneous Academic Sites
Applied Sciences, 2023 Academic researchers publish their work in various formats, such as papers, patents, and research reports, on different academic sites. When searching for a particular researcher’s work, it can be challenging to pinpoint the right individual, especially ...
Dojin Choi +6 more
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Ethnicity-based name partitioning for author name disambiguation using supervised machine learning. [PDF]
J Assoc Inf Sci Technol, 2021 In several author name disambiguation studies, some ethnic name groups such as East Asian names are reported to be more difficult to disambiguate than others.
Kim J, Kim J, Owen-Smith J.
europepmc +2 more sources
ANDez: An open-source tool for author name disambiguation using machine learning
SoftwareXAuthor name disambiguation in bibliographic data is challenging due to the same names of different authors and name variations of authors. Various machine learning (ML) methods address this, but a unified framework for comparing them is lacking.
Jinseok Kim, Jenna Kim
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Toward a New Paradigm for Author Name Disambiguation
IEEE Access, 2022 Author Name Disambiguation (AND) has emerged as a significant challenge in the bibliometric context with the growing volume of scientific literature. When citations written by different authors have the same names (polysemy or homonym names), and when an
Ayesha Manzoor +2 more
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Quantitative Science Studies, 2022 Although several large knowledge graphs have been proposed in the scholarly field, such graphs are limited with respect to several data quality dimensions such as accuracy and coverage.
Michael Färber, Lin Ao
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