{"id":886,"date":"2010-12-08T21:13:24","date_gmt":"2010-12-08T20:13:24","guid":{"rendered":"http:\/\/www.laurentbourrelly.com\/blog\/?p=886"},"modified":"2010-12-08T21:13:24","modified_gmt":"2010-12-08T20:13:24","slug":"loperateur-aroundn-dans-google","status":"publish","type":"post","link":"https:\/\/www.laurentbourrelly.com\/blog\/886.php","title":{"rendered":"L’op\u00e9rateur AROUND(n) dans Google"},"content":{"rendered":"

\"Extrait<\/a>Une petite note rapide pour signaler un nouvel op\u00e9rateur Google.<\/p>\n

Il s’agit de AROUND(n) qui permet d’effectuer une recherche en int\u00e9grant la notion de proximit\u00e9 entre les termes. Peut-\u00eatre que l’algorithme n-gram n’est pas tr\u00e8s loin derri\u00e8re cet op\u00e9rateur.<\/p>\n

C’est l’in\u00e9vitable Barry Schwartz qui nous apprend l’apparition de l’op\u00e9rateur AROUND(n)<\/a>, o\u00f9 (n) sert \u00e0 d\u00e9limiter la proximit\u00e9 entre les termes.<\/p>\n

AROUND(n)<\/h1>\n

Par exemple, la requ\u00eate [mots cl\u00e9s AROUND(10) autres mot cl\u00e9s] va retourner une proximit\u00e9 assez large, tandis que [mot cl\u00e9s AROUND (2) autres mots cl\u00e9s] recherche des termes plus rapproch\u00e9s.<\/p>\n

Par contre, aucune id\u00e9e de l’\u00e9chelle de proximit\u00e9 d\u00e9finie par les chiffres.<\/p>\n

En fait, cet op\u00e9rateur se r\u00e9v\u00e8le utile pour chercher dans des documents tr\u00e8s longs o\u00f9 Google a plus de difficult\u00e9 \u00e0 retourner des relations entre les termes.
\nCela permet d’affiner des requ\u00eates qui retournent pas des r\u00e9sultats satisfaisants au premier abord.<\/p>\n

Attention de bien utiliser AROUND(n) tout en majuscule.
\nEn tout cas, d’apr\u00e8s mes premiers essais, cet op\u00e9rateur Google a l’air plut\u00f4t efficace.<\/p>\n

Bing poss\u00e8de \u00e9galement un op\u00e9rateur \u00e9quivalent avec \u00ab\u00a0near\u00a0\u00bb.<\/p>\n

L’algorithme n-gram<\/h3>\n

Je suppose que l’algorithme n-gram<\/a> n’est pas tr\u00e8s loin derri\u00e8re cet op\u00e9rateur puisqu’il concerne (entre autres) la proximit\u00e9 entre les termes dans le calcul de pertinence. Pour les plus curieux, c’est du c\u00f4t\u00e9 de la Cha\u00eene de Markov qu’il faut regarder pour comprendre la pr\u00e9diction des termes suivants en fonction de ceux saisis.<\/p>\n

Google a annonc\u00e9 depuis longtemps son affection pour l’algorithme n-gram<\/a>, notamment pour la traduction, la reconnaissance vocale, la correction d’orthographe, l’extraction d’information et la d\u00e9tection d’entit\u00e9s.
\nDire que cet algorithme est tr\u00e8s pr\u00e9sent dans la technologie Google est presque redondant.<\/p>\n","protected":false},"excerpt":{"rendered":"

Une petite note rapide pour signaler un nouvel op\u00e9rateur Google. Il s’agit de AROUND(n) qui permet d’effectuer une recherche en int\u00e9grant la notion de proximit\u00e9 entre les termes. Peut-\u00eatre que l’algorithme n-gram n’est pas tr\u00e8s loin derri\u00e8re cet op\u00e9rateur.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","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":"","ast-disable-related-posts":"","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-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":"","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-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":"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":""},"mobile":{"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":""}},"footnotes":""},"categories":[8],"tags":[202],"class_list":["post-886","post","type-post","status-publish","format-standard","hentry","category-moteurs-de-recherche","tag-google"],"_links":{"self":[{"href":"https:\/\/www.laurentbourrelly.com\/blog\/wp-json\/wp\/v2\/posts\/886","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.laurentbourrelly.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.laurentbourrelly.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.laurentbourrelly.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.laurentbourrelly.com\/blog\/wp-json\/wp\/v2\/comments?post=886"}],"version-history":[{"count":0,"href":"https:\/\/www.laurentbourrelly.com\/blog\/wp-json\/wp\/v2\/posts\/886\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.laurentbourrelly.com\/blog\/wp-json\/wp\/v2\/media?parent=886"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.laurentbourrelly.com\/blog\/wp-json\/wp\/v2\/categories?post=886"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.laurentbourrelly.com\/blog\/wp-json\/wp\/v2\/tags?post=886"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}