Le Recall-Oriented Understudy for Gisting Evaluation (ROUGE) est une famille de m\u00e9triques utilis\u00e9e en traitement automatique du langage naturel (TALN) pour \u00e9valuer la qualit\u00e9 des r\u00e9sum\u00e9s g\u00e9n\u00e9r\u00e9s automatiquement. Qu\u2019est-ce que Recall-Oriented Understudy for Gisting Evaluation ? Il s’agit d’un ensemble de m\u00e9triques qui comparent un r\u00e9sum\u00e9 g\u00e9n\u00e9r\u00e9 par une machine \u00e0 un ou plusieurs r\u00e9sum\u00e9s de r\u00e9f\u00e9rence r\u00e9dig\u00e9s par des humains, en se concentrant sur la pr\u00e9sence d’\u00e9l\u00e9ments importants.<\/p>\n
ROUGE calcule le chevauchement entre les unit\u00e9s textuelles (comme les N-grammes, c’est-\u00e0-dire les s\u00e9quences de N mots) du r\u00e9sum\u00e9 g\u00e9n\u00e9r\u00e9 et celles des r\u00e9sum\u00e9s de r\u00e9f\u00e9rence. Diff\u00e9rentes variantes de ROUGE existent (ROUGE-N, ROUGE-L, ROUGE-S) et se concentrent sur diff\u00e9rents aspects du chevauchement\u00a0: les correspondances de N-grammes exacts, la plus longue sous-s\u00e9quence commune ou les skip-bigrammes (paires de mots qui peuvent \u00eatre s\u00e9par\u00e9s par d’autres mots). Imaginez que vous deviez r\u00e9sumer un article de presse. ROUGE compare votre r\u00e9sum\u00e9 \u00e0 un r\u00e9sum\u00e9 id\u00e9al fait par un expert. Plus votre r\u00e9sum\u00e9 contient d’\u00e9l\u00e9ments importants pr\u00e9sents dans le r\u00e9sum\u00e9 id\u00e9al, meilleur sera votre score ROUGE. L’accent est mis sur le recall<\/em>, c’est-\u00e0-dire sur la capacit\u00e9 du syst\u00e8me \u00e0 retrouver les informations importantes du texte original.<\/p>\n ROUGE est un outil essentiel en IA et en prompt engineering car il permet d’\u00e9valuer et d’am\u00e9liorer les performances des mod\u00e8les de r\u00e9sum\u00e9 automatique. Il fournit une mesure quantitative de la qualit\u00e9 d’un r\u00e9sum\u00e9, permettant ainsi de comparer diff\u00e9rentes approches et d’optimiser les prompts pour obtenir des r\u00e9sum\u00e9s plus pr\u00e9cis et complets. Par exemple, en \u00e9valuant les r\u00e9sum\u00e9s g\u00e9n\u00e9r\u00e9s avec ROUGE, on peut ajuster les instructions donn\u00e9es \u00e0 un mod\u00e8le pour qu’il se concentre davantage sur les informations cl\u00e9s d’un texte.<\/p>\n Le Recall-Oriented Understudy for Gisting Evaluation (ROUGE) est une famille de m\u00e9triques utilis\u00e9e en traitement automatique du langage naturel (TALN) pour \u00e9valuer la qualit\u00e9 des r\u00e9sum\u00e9s g\u00e9n\u00e9r\u00e9s automatiquement. Qu\u2019est-ce que Recall-Oriented Understudy for Gisting Evaluation ? Il s’agit d’un ensemble de m\u00e9triques qui comparent un r\u00e9sum\u00e9 g\u00e9n\u00e9r\u00e9 par une machine \u00e0 un ou plusieurs r\u00e9sum\u00e9s […]<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[59],"tags":[628,666,667,80],"class_list":["post-1186","post","type-post","status-publish","format-standard","hentry","category-r","tag-n-grammes","tag-recall-oriented-understudy-for-gisting-evaluation","tag-resume-automatique","tag-traitement-automatique-du-langage-naturel-taln"],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"","author_link":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/author\/"},"uagb_comment_info":0,"uagb_excerpt":"Le Recall-Oriented Understudy for Gisting Evaluation (ROUGE) est une famille de m\u00e9triques utilis\u00e9e en traitement automatique du langage naturel (TALN) pour \u00e9valuer la qualit\u00e9 des r\u00e9sum\u00e9s g\u00e9n\u00e9r\u00e9s automatiquement. Qu\u2019est-ce que Recall-Oriented Understudy for Gisting Evaluation ? Il s’agit d’un ensemble de m\u00e9triques qui comparent un r\u00e9sum\u00e9 g\u00e9n\u00e9r\u00e9 par une machine \u00e0 un ou plusieurs r\u00e9sum\u00e9s\u2026","_links":{"self":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts\/1186","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/comments?post=1186"}],"version-history":[{"count":0,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts\/1186\/revisions"}],"wp:attachment":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/media?parent=1186"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/categories?post=1186"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/tags?post=1186"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Pourquoi Recall-Oriented Understudy for Gisting Evaluation est-il important\u00a0?<\/h3>\n
Termes associ\u00e9s<\/h3>\n
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