{"id":2747,"date":"2021-05-11T17:58:00","date_gmt":"2021-05-11T17:58:00","guid":{"rendered":"https:\/\/www.science-metrix.com\/?p=2747"},"modified":"2021-09-29T15:12:15","modified_gmt":"2021-09-29T15:12:15","slug":"article-level-classification-of-scientific-publications-a-comparison-of-deep-learning-direct-citation-and-bibliographic-coupling","status":"publish","type":"post","link":"https:\/\/www.science-metrix.com\/fr\/article-level-classification-of-scientific-publications-a-comparison-of-deep-learning-direct-citation-and-bibliographic-coupling\/","title":{"rendered":"Article-level classification of scientific publications: A comparison of deep learning, direct citation and bibliographic coupling"},"content":{"rendered":"
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Article-level classification of scientific publications: A comparison of deep learning, direct citation and bibliographic coupling<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Rivest, M., Vignola-Gagn\u00e9, E., et Archambault, E. (2021). Article-level classification of scientific publications: A comparison of deep learning, direct citation and bibliographic coupling. PLoS ONE<\/em>, 16<\/em>(5), e0251493. https:\/\/doi.org\/10.1371\/journal.pone.0251493<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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R\u00e9sum\u00e9<\/strong><\/p>

Les classifications des activit\u00e9s de recherche et des publications scientifiques sont fondamentales aux \u00e9valuations de telles activit\u00e9s, tant au niveau des organismes qu\u2019au niveau des gouvernements. Il existe plusieurs classifications actuellement en usage, et chacune d\u2019elles doit continuellement \u00eatre mise \u00e0 jour en faisant usage de techniques \u00e0 la fine pointe et en int\u00e9grant des nouveaux champs de recherche en \u00e9mergence. Les r\u00e9seaux de neurones convolutifs, une composante de l\u2019apprentissage profond, ont r\u00e9cemment permis de cat\u00e9goriser des corpus de textes volumineux de mani\u00e8re novatrice et tr\u00e8s performante. Cet article compare une technique d\u2019apprentissage profond qui cat\u00e9gorise plus de 40 millions d\u2019articles scientifiques et des dizaines de milliers de revues scientifiques. Il la compare \u00e0 des techniques de couplage bibliographique, de citations directes et de classification manuelle, des approches couramment utilis\u00e9es en bibliom\u00e9trie et dans un contexte de politiques propres aux S&T, telles que l\u2019octroi de financement. Les r\u00e9sultats d\u00e9montrent que le rendement d\u2019une approche par apprentissage profond est semblable aux approches bibliom\u00e9triques fond\u00e9es sur la th\u00e9orie des graphes. Toutes les approches \u00e9valu\u00e9es dans cet article se comparent \u00e9galement \u00e0 la classification manuelle. Cependant, les approches automatis\u00e9es ne performaient que l\u00e9g\u00e8rement mieux que la strat\u00e9gie fond\u00e9e sur les citations directes, qui correspond \u00e0 une approche simple de propagation des \u00e9tiquettes. En conclusion, l\u2019apprentissage profond est une approche prometteuse puisqu\u2019elle performe aussi bien que les autres alors qu\u2019elle n\u2019a toujours pas atteint son potentiel de perfectionnement. Par exemple, un r\u00e9seau de neurones convolutif int\u00e9grant de l\u2019information provenant d\u2019un r\u00e9seau de citations est vraisemblablement la cl\u00e9 pour d\u00e9velopper un algorithme de classification encore plus performant.<\/p>

Pour lire l'article<\/a>.<\/p>

Image : Par Christa Dodoo<\/a> \u00e0 Unsplash<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t

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PLoS ONE<\/p>","protected":false},"author":2,"featured_media":2748,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[9],"tags":[14,41],"class_list":["post-2747","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-peer-reviewed-papers","tag-bibliometrics","tag-classification"],"yoast_head":"\nArticle-level classification of scientific publications: A comparison of deep learning, direct citation and bibliographic coupling - Science-Metrix<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wp135259.wpdns.ca\/article-level-classification-of-scientific-publications-a-comparison-of-deep-learning-direct-citation-and-bibliographic-coupling\/\" \/>\n<meta property=\"og:locale\" content=\"fr_CA\" 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