En intelligence artificielle et en prompt engineering, la similarit\u00e9 cosinus mesure la ressemblance entre deux morceaux de texte. Qu\u2019est-ce que la similarit\u00e9 cosinus ? C\u2019est une m\u00e9trique qui quantifie la similarit\u00e9 entre deux vecteurs en calculant le cosinus de l’angle entre eux.<\/p>\n
Imaginez deux fl\u00e8ches pointant dans des directions diff\u00e9rentes. Si les fl\u00e8ches pointent dans la m\u00eame direction, l’angle entre elles est de 0 degr\u00e9 et le cosinus de 0 est 1, indiquant une similarit\u00e9 parfaite. Si les fl\u00e8ches pointent dans des directions oppos\u00e9es, l’angle est de 180 degr\u00e9s et le cosinus est -1, indiquant une opposition totale. Appliqu\u00e9 au texte, chaque mot est une dimension et chaque texte est repr\u00e9sent\u00e9 par un vecteur dans un espace multidimensionnel. La similarit\u00e9 cosinus calcule le cosinus de l’angle entre ces vecteurs.<\/p>\n
La similarit\u00e9 cosinus est cruciale pour de nombreuses t\u00e2ches en IA, notamment la recherche d’informations, la classification de textes et les syst\u00e8mes de recommandation. En prompt engineering, elle permet d’\u00e9valuer la pertinence d’une r\u00e9ponse g\u00e9n\u00e9r\u00e9e par un mod\u00e8le de langage par rapport \u00e0 une requ\u00eate. Par exemple, si vous demandez \u00e0 un chatbot de vous r\u00e9sumer un article, la similarit\u00e9 cosinus peut \u00eatre utilis\u00e9e pour comparer le r\u00e9sum\u00e9 g\u00e9n\u00e9r\u00e9 avec l’article original et ainsi \u00e9valuer la qualit\u00e9 du r\u00e9sum\u00e9. Plus le score de similarit\u00e9 est proche de 1, plus les textes sont similaires. <\/p>\n
En intelligence artificielle et en prompt engineering, la similarit\u00e9 cosinus mesure la ressemblance entre deux morceaux de texte. Qu\u2019est-ce que la similarit\u00e9 cosinus ? C\u2019est une m\u00e9trique qui quantifie la similarit\u00e9 entre deux vecteurs en calculant le cosinus de l’angle entre eux. Comment fonctionne la similarit\u00e9 cosinus ? Imaginez deux fl\u00e8ches pointant dans des directions […]<\/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":[94],"tags":[16,459,185,458,80,416],"class_list":["post-838","post","type-post","status-publish","format-standard","hentry","category-s","tag-apprentissage-automatique-machine-learning","tag-distance-euclidienne","tag-similarite-cosinus","tag-tf-idf","tag-traitement-automatique-du-langage-naturel-taln","tag-word-embeddings"],"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":"En intelligence artificielle et en prompt engineering, la similarit\u00e9 cosinus mesure la ressemblance entre deux morceaux de texte. Qu\u2019est-ce que la similarit\u00e9 cosinus ? C\u2019est une m\u00e9trique qui quantifie la similarit\u00e9 entre deux vecteurs en calculant le cosinus de l’angle entre eux. Comment fonctionne la similarit\u00e9 cosinus ? Imaginez deux fl\u00e8ches pointant dans des directions\u2026","_links":{"self":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts\/838","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=838"}],"version-history":[{"count":1,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts\/838\/revisions"}],"predecessor-version":[{"id":1029,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/posts\/838\/revisions\/1029"}],"wp:attachment":[{"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/media?parent=838"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/categories?post=838"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/happynumeric.com\/lexique-intelligence-artificielle\/wp-json\/wp\/v2\/tags?post=838"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}