{"id":11578,"date":"2020-10-08T14:43:50","date_gmt":"2020-10-08T14:43:50","guid":{"rendered":"https:\/\/datascientest.com\/?p=11578"},"modified":"2023-11-09T14:11:48","modified_gmt":"2023-11-09T14:11:48","slug":"tf-idf-intelligence-artificielle","status":"publish","type":"post","link":"https:\/\/datascientest.com\/tf-idf-intelligence-artificielle","title":{"rendered":"Intelligence artificielle: R\u00e9sumer un texte gr\u00e2ce au TF IDF"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"11578\" class=\"elementor elementor-11578\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-81afcdd elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"81afcdd\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8b6a6cf\" data-id=\"8b6a6cf\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-97ac255 elementor-widget elementor-widget-text-editor\" data-id=\"97ac255\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<h2><span style=\"color: #000000;\">Les nombreux progr\u00e8s en\u00a0<\/span><a href=\"https:\/\/datascientest.com\/introduction-au-nlp-natural-language-processing\" target=\"_blank\" rel=\"noopener\">NLP\u00a0<\/a><span style=\"color: #000000;\">permettent \u00e0 ce jour de\u00a0 l\u2019appliquer \u00e0 de nombreuses t\u00e2ches\u00a0: traduction, g\u00e9n\u00e9ration de texte, r\u00e9sum\u00e9\u2026 Dans cet article, nous allons aborder un aspect simple du r\u00e9sum\u00e9\u00a0: le <\/span>r\u00e9sum\u00e9 extractif<span style=\"color: #000000;\">. Il ne s\u2019agit pas d\u2019un r\u00e9sum\u00e9 de synth\u00e8se mais plut\u00f4t d\u2019une extraction des phrases les plus int\u00e9ressantes, porteuses de sens.\u00a0<\/span><\/h2>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-025e835 elementor-widget elementor-widget-text-editor\" data-id=\"025e835\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\tNous allons pour cela introduire la notion de TF-IDF qui est au c\u0153ur de l\u2019algorithme pour r\u00e9sumer, puis nous allons ensuite \u00e9tudier pas \u00e0 pas les \u00e9tapes qui permettent de r\u00e9sumer.\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f721944 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f721944\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-b5af977\" data-id=\"b5af977\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4776498 elementor-widget elementor-widget-heading\" data-id=\"4776498\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h3 class=\"elementor-heading-title elementor-size-default\">Qu\u2019est ce TF-IDF ? D\u00e9finition<\/h3>\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-a72415f elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a72415f\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-e1caf3a\" data-id=\"e1caf3a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-85c8fdb elementor-widget elementor-widget-text-editor\" data-id=\"85c8fdb\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"color: #000000;\"><b><i>Term Frequency \u2013 Inverse Document Frequency <\/i><\/b><b>est une mesure qui permet, \u00e0 partir d\u2019un ensemble de textes, de conna\u00eetre l\u2019importance relative de chaque mot.<\/b><\/span><\/p><blockquote><p><span style=\"color: #000000;\"><b> <\/b><span style=\"font-weight: 400;\">La mauvaise id\u00e9e serait de penser que plus un mot est fr\u00e9quent et plus il est important dans une phrase. <\/span><\/span><\/p><\/blockquote><p><span style=\"color: #000000;\"><span style=\"font-weight: 400;\">Or, avec cela, on se retrouverait tr\u00e8s vite avec des mots cl\u00e9s tels que \u00ab\u00a0le\u00a0\u00bb, \u00ab\u00a0du\u00a0\u00bb, \u00ab\u00a0a\u00a0\u00bb\u2026 qui sont tout sauf utiles\u00a0! TF-IDF permet de rectifier cela.<\/span><\/span><\/p><p><span style=\"color: #000000;\"><span style=\"font-weight: 400;\">A partir de maintenant, imaginez que nous avons un <\/span><b>ensemble de textes <\/b><span style=\"font-weight: 400;\">(par exemple l\u2019ensemble des \u0153uvres de Moli\u00e8re). Et nous voulons extraire les mots les plus importants de ses \u0153uvres.\u00a0<\/span><\/span><\/p><p><span style=\"font-weight: 400; color: #000000;\">TF permet de mesurer l\u2019importance relative d\u2019un mot dans un document, par exemple, quelle est l\u2019importance de pingre dans l\u2019avare. Elle est d\u00e9finie par la formule\u00a0<\/span><span style=\"color: #000000;\">\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c38e66f elementor-widget elementor-widget-image\" data-id=\"c38e66f\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"300\" height=\"64\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/Capture-de\u0301cran-2020-10-08-a\u0300-15.04.26-300x64.png\" class=\"attachment-medium size-medium wp-image-11865\" alt=\"formule\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/Capture-de\u0301cran-2020-10-08-a\u0300-15.04.26-300x64.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/Capture-de\u0301cran-2020-10-08-a\u0300-15.04.26.png 472w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-705ed72 elementor-widget elementor-widget-text-editor\" data-id=\"705ed72\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><em><span style=\"color: #000000;\"><span style=\"font-weight: 400;\">o\u00f9\u00a0 <\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">i l<\/span><span style=\"font-weight: 400;\">e mot et<\/span><span style=\"font-weight: 400;\"> j <\/span><span style=\"font-weight: 400;\">le document<\/span> <span style=\"font-weight: 400;\">\u00a0<\/span><span style=\"font-weight: 400;\">L<\/span><span style=\"font-weight: 400;\"><sub>j\u00a0<\/sub> <\/span><span style=\"font-weight: 400;\">le nombre total de mot dans le texte<\/span><span style=\"font-weight: 400;\"> j<\/span> <span style=\"font-weight: 400;\">Freq<\/span><span style=\"font-weight: 400;\">i,j<\/span> <span style=\"font-weight: 400;\">la fr\u00e9quence du mot<\/span><span style=\"font-weight: 400;\"> i dans le doc j<\/span><\/span><\/em><\/p><p><span style=\"font-weight: 400; color: #000000;\">i le mot et j le document\u00a0 L<sub>j<\/sub>\u00a0 le nombre total de mot dans le texte j Freqi,j la fr\u00e9quence du mot .\u00a0<\/span><\/p><blockquote><p><span style=\"color: #000000;\"><span style=\"font-weight: 400;\">IDF <\/span><span style=\"font-weight: 400;\">mesure la signification d&rsquo;un terme non pas en fonction de sa fr\u00e9quence dans un document particulier, mais en fonction de sa\u00a0<\/span><span style=\"font-weight: 400;\">distribution et de son utilisation dans l&rsquo;ensemble des documents<\/span><span style=\"font-weight: 400;\">. <\/span><\/span><b>Plus un terme a de potentiel, plus l\u2019Inverse Document Frequency est \u00e9lev\u00e9e<\/b><span style=\"color: #000000;\"><span style=\"font-weight: 400;\">. <\/span><\/span><\/p><\/blockquote><p><span style=\"color: #000000;\"><span style=\"font-weight: 400;\">Id\u00e9alement, un\u00a0<\/span><span style=\"font-weight: 400;\">terme appara\u00eet tr\u00e8s fr\u00e9quemment dans quelques textes seulement<\/span><span style=\"font-weight: 400;\">. Les mots qui apparaissent dans presque tous les documents ou tr\u00e8s rarement n&rsquo;ont que peu d&rsquo;importance. On obtient le score par la formule suivante\u00a0:\u00a0<\/span><\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7da7d45 elementor-widget elementor-widget-image\" data-id=\"7da7d45\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"300\" height=\"72\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/Capture-de\u0301cran-2020-10-08-a\u0300-15.08.15-300x72.png\" class=\"attachment-medium size-medium wp-image-11866\" alt=\"formule\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/Capture-de\u0301cran-2020-10-08-a\u0300-15.08.15-300x72.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/Capture-de\u0301cran-2020-10-08-a\u0300-15.08.15.png 414w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0afff0a elementor-widget elementor-widget-text-editor\" data-id=\"0afff0a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><em><span style=\"color: #000000;\"><span style=\"font-weight: 400;\">o\u00f9\u00a0 <\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">N<\/span><span style=\"font-weight: 400;\"><sub>D<\/sub><\/span><span style=\"font-weight: 400;\"> le nombre total de documents dans le corpus <\/span><span style=\"font-weight: 400;\">\u00a0<\/span><span style=\"font-weight: 400;\">f<\/span><span style=\"font-weight: 400;\"><sub>i<\/sub><\/span><span style=\"font-weight: 400;\"> nombre de documents o\u00f9 le mot i appara\u00eet <\/span><span style=\"font-weight: 400;\">\u00a0<\/span><\/span><\/em><\/p><p><span style=\"font-weight: 400; color: #000000;\">On prend le logarithme car pour un gros corpus, la valeur de ce terme peut exploser.<\/span><\/p><p><span style=\"color: #000000;\"><span style=\"font-weight: 400;\">Une fois les deux termes calcul\u00e9s, on calcule sa valeur par :<\/span><\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f841c5c elementor-widget elementor-widget-image\" data-id=\"f841c5c\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"300\" height=\"52\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/Capture-de\u0301cran-2020-10-08-a\u0300-15.09.37-300x52.png\" class=\"attachment-medium size-medium wp-image-11867\" alt=\"formule\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/Capture-de\u0301cran-2020-10-08-a\u0300-15.09.37-300x52.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/Capture-de\u0301cran-2020-10-08-a\u0300-15.09.37.png 646w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ea56e0b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ea56e0b\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-9105089\" data-id=\"9105089\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-67bcee3 elementor-widget elementor-widget-heading\" data-id=\"67bcee3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Nettoyer, nettoyer\u2026<\/h3>\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-50b066a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"50b066a\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-6735882\" data-id=\"6735882\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-748508b elementor-widget elementor-widget-text-editor\" data-id=\"748508b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Le plus laborieux et chronophage en <b>NLP<\/b> est le <b>preprocessing <\/b>&#8211; la t\u00e2che qui consiste \u00e0<b> travailler notre dataset<\/b> pour qu\u2019il puisse \u00eatre exploit\u00e9 efficacement. Il faut penser \u00e0 harmoniser le texte au maximum pour faciliter la t\u00e2che de l\u2019algorithme. Les \u00e9tapes les plus importantes pour notre \u00e9tude de cas sont :\u00a0<\/p><ul><li>Remplacer les caract\u00e8res sp\u00e9ciaux par des espaces\u00a0<\/li><li>Remplacer des espaces suppl\u00e9mentaires en un espace classique<\/li><\/ul><p>Pour ce faire, nous utilisons la\u00a0<a href=\"https:\/\/www.nltk.org\/\" target=\"_blank\" rel=\"noopener\">librairie NLTK\u00a0<\/a>et <b>Re<\/b>.\u00a0<\/p>\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-867750c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"867750c\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-912cbcb\" data-id=\"912cbcb\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-fe444af elementor-widget elementor-widget-shortcode\" data-id=\"fe444af\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/guipet\/9042187a5367fa1e9c58dd22b0c14427.js\"><\/script><\/div>\n\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-005465d elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"005465d\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d037e1f\" data-id=\"d037e1f\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-ea5de2b elementor-widget elementor-widget-heading\" data-id=\"ea5de2b\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Calculer TF-IDF<\/h3>\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-23d88fb elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"23d88fb\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-862cd5c\" data-id=\"862cd5c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-177b7f3 elementor-widget elementor-widget-text-editor\" data-id=\"177b7f3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Le calcul dans l\u2019id\u00e9e est simple, mais il faut pr\u00eater attention au code. Il faut commencer par <\/span><b>cr\u00e9er un vocabulaire <\/b><span style=\"font-weight: 400;\">de tout notre corpus. Ensuite, il faut <\/span><b>cr\u00e9er<\/b><span style=\"font-weight: 400;\"> ce qu\u2019on appelle une <\/span><b><i>count matrix<\/i><\/b><span style=\"font-weight: 400;\"> qui <\/span><b>pour chaque document compte l\u2019occurrence de chaque mot<\/b><span style=\"font-weight: 400;\">. <\/span><\/p>\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-7d03db7 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7d03db7\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-756c61d\" data-id=\"756c61d\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4d65d0e elementor-widget elementor-widget-image\" data-id=\"4d65d0e\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"466\" height=\"289\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/unnamed.png\" class=\"attachment-large size-large wp-image-11585\" alt=\"TF IDF\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/unnamed.png 466w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/unnamed-300x186.png 300w\" sizes=\"(max-width: 466px) 100vw, 466px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Count Matrix<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1db16f0 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1db16f0\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-43b6f7d\" data-id=\"43b6f7d\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-ffcc42a elementor-widget elementor-widget-text-editor\" data-id=\"ffcc42a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400; color: #000000;\">Une fois cette matrice cr\u00e9\u00e9e, on peut calculer le score TF-IDF de cette matrice.\u00a0<\/span><\/p><p><b>On finit par construire un dictionnaire qui associe la valeur TF-IDF \u00e0 chaque mot.<\/b><\/p>\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-67079a8 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"67079a8\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-a17aed7\" data-id=\"a17aed7\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-cd35edf elementor-widget elementor-widget-heading\" data-id=\"cd35edf\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Le r\u00e9sum\u00e9<\/h3>\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ae984df elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ae984df\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-505e2c7\" data-id=\"505e2c7\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-add8c4e elementor-widget elementor-widget-text-editor\" data-id=\"add8c4e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400; color: #000000;\">On va calculer le score de chaque phrase des documents bas\u00e9 sur la valeur TF-IDF de chaque mot qui la compose.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f148d9b elementor-widget elementor-widget-shortcode\" data-id=\"f148d9b\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/guipet\/4747abed8d30a8075ec9d53bf9422c01.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d112d6e elementor-widget elementor-widget-text-editor\" data-id=\"d112d6e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Une fois le score de chaque phrase obtenue, on peut faire un r\u00e9sum\u00e9 d\u2019un texte.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ce855fd elementor-widget elementor-widget-shortcode\" data-id=\"ce855fd\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/guipet\/22e4040122f1cff6a3e758b0198279c5.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f5b6c10 elementor-widget elementor-widget-text-editor\" data-id=\"f5b6c10\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\"><span style=\"color: #000000;\">Voici un exemple de r\u00e9sultat sur un texte\u00a0:<\/span><\/span><\/p>\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-999a6a3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"999a6a3\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-f44982e\" data-id=\"f44982e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-b24b29d elementor-widget elementor-widget-image\" data-id=\"b24b29d\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"512\" height=\"122\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/unnamed-1.png\" class=\"attachment-large size-large wp-image-11586\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/unnamed-1.png 512w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/unnamed-1-300x71.png 300w\" sizes=\"(max-width: 512px) 100vw, 512px\" \/>\t\t\t\t\t\t\t\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-71476c3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"71476c3\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-635c5a0\" data-id=\"635c5a0\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4b791c9 elementor-widget elementor-widget-text-editor\" data-id=\"4b791c9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Le r\u00e9sum\u00e9 est d\u00e9j\u00e0 de qualit\u00e9 convenable. Comme on peut le voir, il nous a fallu quelques fonctions et ne pas se perdre dans le code pour calculer le score de chaque mot. Tout est question d\u2019organisation. <\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">Cependant, cela reste un r\u00e9sum\u00e9 assez classique. Des nouvelles m\u00e9thodes comme les <\/span><b>Transformers<\/b><span style=\"font-weight: 400;\">, ou des m\u00e9thodes plus classiques comme les <\/span><b>n-gram<\/b><span style=\"font-weight: 400;\">, permettent de r\u00e9aliser de <\/span><i><span style=\"font-weight: 400;\">vrais<\/span><\/i><span style=\"font-weight: 400;\"> r\u00e9sum\u00e9s.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Cependant, cela devient plus compliqu\u00e9 et n\u00e9cessite un r\u00e9el background en terme de connaissances et d\u2019applications. Notre formation s\u2019est d\u2019ailleurs dot\u00e9e, r\u00e9cemment, de cours sur ces nouvelles m\u00e9thodes, pour permettre de \u00e0 ses utilisateurs de r\u00e9aliser des projets avec une plus grande ambition!\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7a099cf elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"7a099cf\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formations-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">D\u00e9couvrir nos formations<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\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\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Les nombreux progr\u00e8s en&nbsp;NLP&nbsp;permettent \u00e0 ce jour de&nbsp; l\u2019appliquer \u00e0 de nombreuses t\u00e2ches&nbsp;: traduction, g\u00e9n\u00e9ration de texte, r\u00e9sum\u00e9\u2026 Dans cet article, nous allons aborder un aspect simple du r\u00e9sum\u00e9&nbsp;: le r\u00e9sum\u00e9 extractif. Il ne s\u2019agit pas d\u2019un r\u00e9sum\u00e9 de synth\u00e8se mais plut\u00f4t d\u2019une extraction des phrases les plus int\u00e9ressantes, porteuses de sens.&nbsp; Nous allons pour [&hellip;]<\/p>\n","protected":false},"author":78,"featured_media":11742,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2497],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Intelligence artificielle: R\u00e9sumer un texte gr\u00e2ce au TF IDF<\/title>\n<meta name=\"description\" content=\"Intelligence Artificielle : D\u00e9couvrez la notion de TF-IDF au c\u0153ur de l\u2019algorithme de NLP qui permet de r\u00e9sumer des textes !\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascientest.com\/tf-idf-intelligence-artificielle\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Intelligence artificielle: R\u00e9sumer un texte gr\u00e2ce au TF IDF\" \/>\n<meta property=\"og:url\" content=\"https:\/\/datascientest.com\/tf-idf-intelligence-artificielle\" \/>\n<meta property=\"og:site_name\" content=\"Formation Data Science | DataScientest.com\" \/>\n<meta property=\"article:published_time\" content=\"2020-10-08T14:43:50+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-11-09T14:11:48+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/10\/illu_resumer_blog-06.png\" \/>\n\t<meta property=\"og:image:width\" content=\"6334\" \/>\n\t<meta property=\"og:image:height\" content=\"2500\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"J\u00e9r\u00e9my Robert\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u00c9crit par\" \/>\n\t<meta name=\"twitter:data1\" content=\"J\u00e9r\u00e9my Robert\" \/>\n\t<meta name=\"twitter:label2\" content=\"Dur\u00e9e de lecture estim\u00e9e\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/datascientest.com\/tf-idf-intelligence-artificielle\",\"url\":\"https:\/\/datascientest.com\/tf-idf-intelligence-artificielle\",\"name\":\"Intelligence artificielle: R\u00e9sumer un texte gr\u00e2ce au TF IDF\",\"isPartOf\":{\"@id\":\"https:\/\/datascientest.com\/#website\"},\"datePublished\":\"2020-10-08T14:43:50+00:00\",\"dateModified\":\"2023-11-09T14:11:48+00:00\",\"author\":{\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/7af2361c48e24e79a8aa2360e6e74925\"},\"description\":\"Intelligence Artificielle : D\u00e9couvrez la notion de TF-IDF au c\u0153ur de l\u2019algorithme de NLP qui permet de r\u00e9sumer des textes !\",\"inLanguage\":\"fr-FR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/datascientest.com\/tf-idf-intelligence-artificielle\"]}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/datascientest.com\/#website\",\"url\":\"https:\/\/datascientest.com\/\",\"name\":\"Formation Data Science | DataScientest.com\",\"description\":\"Leader de la formation en Data Science\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/datascientest.com\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"fr-FR\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/7af2361c48e24e79a8aa2360e6e74925\",\"name\":\"J\u00e9r\u00e9my Robert\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"fr-FR\",\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/11\/jeremyrobert.jpeg\",\"contentUrl\":\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/11\/jeremyrobert.jpeg\",\"caption\":\"J\u00e9r\u00e9my Robert\"},\"description\":\"J\u00e9r\u00e9my Robert est actuellement Directeur p\u00e9dagogique B2B chez DataScientest.com. 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