On the combination of domain-specific heuristics for author name disambiguation : the nearest cluster method.

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dc.contributor.authorSantana, Alan Filipe
dc.contributor.authorGonçalves, André Gonçalves
dc.contributor.authorLaender, Alberto Henrique Frade
dc.contributor.authorFerreira, Anderson Almeida
dc.date.accessioned2017-01-20T14:18:03Z
dc.date.available2017-01-20T14:18:03Z
dc.date.issued2015
dc.description.abstractAuthor name disambiguation has been one of the hardest problems faced by digital libraries since their early days. Historically, supervised solutions have empirically outperformed those based on heuristics, but with the burden of having to rely on manually labeled training sets for the learning process. Moreover, most supervised solutions just apply some type of generic machine learning solution and do not exploit specific knowledge about the problem. In this article, we follow a similar reasoning, but in the opposite direction. Instead of extending an existing supervised solution, we propose a set of carefully designed heuristics and similarity functions, and apply supervision only to optimize such parameters for each particular dataset. As our experiments show, the result is a very effective, efficient and practical author name disambiguation method that can be used in many different scenarios. In fact, we show that our method can beat state-of-the-art supervised methods in terms of effectiveness in many situations while being orders of magnitude faster. It can also run without any training information, using only default parameters, and still be very competitive when compared to these supervised methods (beating several of them) and better than most existing unsupervised author name disambiguation solutions.pt_BR
dc.identifier.citationSANTANA, A. F. et al. On the combination of domain-specific heuristics for auhor name disambiguation : the nearest cluster method. International Journal on Digital Libraries, n. 16, p. 229-246, 2015. Disponível em: <https://link.springer.com/article/10.1007/s00799-015-0158-y>. Acesso em: 20 jan. 2017.pt_BR
dc.identifier.doihttps://doi.org/10.1007/s00799-015-0158-y
dc.identifier.issn1432-1300
dc.identifier.urihttp://www.repositorio.ufop.br/handle/123456789/7140
dc.identifier.uri2https://link.springer.com/article/10.1007/s00799-015-0158-ypt_BR
dc.language.isopt_BRpt_BR
dc.rightsabertopt_BR
dc.subjectSupervised methodspt_BR
dc.titleOn the combination of domain-specific heuristics for author name disambiguation : the nearest cluster method.pt_BR
dc.typeArtigo publicado em periodicopt_BR
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