Cost-effective on-demand associative author name disambiguation [PDF]
Information Processing and Management, 2012 Authorship disambiguation is an urgent issue that affects the quality of digital library services and for which supervised solutions have been proposed, delivering state-of-the-art effectiveness. However, particular challenges such as the prohibitive cost of labeling vast amounts of examples (there are many ambiguous authors), the huge hypothesis space
Alberto Laender +2 more
exaly +7 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
doaj +4 more sources
A Survey of Author Name Disambiguation Techniques of Academic Papers [PDF]
Nongye tushu qingbao xuebao, 2022 [Purpose/Significance] This paper investigates the research on author name disambiguation published in recent years, and reviews the development context of relevant research from the perspective of the impact of data on author name disambiguation methods,
WANG Xin, LU Yao, YUAN Xue, ZHAO Wanjing, CHEN Li, LIU Minjuan
doaj +2 more sources
Effect of forename string on author name disambiguation [PDF]
Journal of the Association for Information Science and Technology, 2019 AbstractIn author name disambiguation, author forenames are used to decide which name instances are disambiguated together and how much they are likely to refer to the same author. Despite such a crucial role of forenames, their effect on the performance of heuristic (string matching) and algorithmic disambiguation is not well understood.
Jinseok Kim 0001, Jenna Kim
openaire +6 more sources
The Impact of Name-Matching and Blocking on Author Disambiguation [PDF]
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018 In this work, we address the problem of blocking in the context of author name disambiguation. We describe a framework that formalizes different ways of name-matching to determine which names could potentially refer to the same author. We focus on name variations that follow from specifying a name with different completeness (i.e.
Tobias Backes, Backes, Tobias
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PubMed knowledge graph 2.0: Connecting papers, patents, and clinical trials in biomedical science [PDF]
Scientific DataPapers, patents, and clinical trials are essential scientific resources in biomedicine, crucial for knowledge sharing and dissemination. However, these documents are often stored in disparate databases with varying management standards and data formats ...
Jian Xu +8 more
doaj +2 more sources
Aggregating large-scale databases for PubMed author name disambiguation [PDF]
Journal of the American Medical Informatics Association: JAMIA, 2021 Yong Huang, Wei Lu
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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
A brief survey of automatic methods for author name disambiguation [PDF]
ACM SIGMOD Record, 2012 Name ambiguity in the context of bibliographic citation records is a hard problem that affects the quality of services and content in digital libraries and similar systems. The challenges of dealing with author name ambiguity have led to a myriad of disambiguation methods.
Anderson A. Ferreira +2 more
core +4 more sources
Data sets for author name disambiguation: an empirical analysis and a new resource [PDF]
Scientometrics, 2017 Mark-Christoph Müller +2 more
exaly +2 more sources