{"id":5996,"date":"2020-07-22T08:01:26","date_gmt":"2020-07-22T07:01:26","guid":{"rendered":"https:\/\/datascientest.com\/?p=5996"},"modified":"2024-01-31T09:30:14","modified_gmt":"2024-01-31T09:30:14","slug":"introduction-au-nlp-natural-language-processing","status":"publish","type":"post","link":"https:\/\/datascientest.com\/introduction-au-nlp-natural-language-processing","title":{"rendered":"Natural Language Processing (NLP) : D\u00e9finition et principes"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"5996\" class=\"elementor elementor-5996\" 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-abacaab elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"abacaab\" 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-0e50d3d\" data-id=\"0e50d3d\" 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-69a1ca7 elementor-widget elementor-widget-text-editor\" data-id=\"69a1ca7\" 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><strong><span style=\"font-size: 18px;\">Vous \u00eates-vous d\u00e9j\u00e0 demand\u00e9 comment des assistants personnels IA tels que Siri ou Cortana fonctionnent ? Comment votre correcteur d\u2019orthographe a \u00e9t\u00e9 capable de d\u00e9tecter des erreurs de syntaxe que vous-m\u00eame n\u2019auriez pas rep\u00e9r\u00e9es ? Comment votre moteur de recherche r\u00e9ussit \u00e0 deviner les mots que vous \u00e9tiez sur le point d\u2019\u00e9crire d\u00e8s les premi\u00e8res lettres ?<\/span><\/strong><\/h2><h2><span style=\"font-weight: 400; font-size: 18px;\">Si ces outils sont utilis\u00e9s \u00e0 des fins radicalement diff\u00e9rentes, ils <strong>reposent tous sur des m\u00e9thodes communes<\/strong>\u00a0: celles du <\/span><strong><i><span style=\"font-size: 18px;\">Natural Language Processing (NLP)<\/span><\/i><\/strong><span style=\"font-weight: 400;\"> ou <\/span><strong><i><span style=\"font-size: 18px;\">Traitement Automatique du Langage Naturel (TALN)<\/span><\/i><\/strong><span style=\"font-weight: 400;\"> en fran\u00e7ais.<\/span><\/h2><h2><span style=\"font-weight: 400; font-size: 18px;\">L\u2019objectif de cet article est de donner un aper\u00e7u global du <\/span><i><span style=\"font-weight: 400; font-size: 18px;\">NLP<\/span><\/i><span style=\"font-weight: 400; font-size: 18px;\">. Plus pr\u00e9cis\u00e9ment, \u00e0 la fin de votre lecture, vous saurez\u00a0:<\/span><\/h2><ul><li style=\"font-weight: 400; font-size: 18px;\"><h2><span style=\"font-weight: 400; font-size: 18px;\">Qu\u2019est-ce que c\u2019est le <\/span><i><span style=\"font-weight: 400; font-size: 18px;\">NLP<\/span><\/i><span style=\"font-weight: 400;\">\u00a0?<\/span><\/h2><\/li><li style=\"font-weight: 400;\"><h2><span style=\"font-weight: 400; font-size: 18px;\">Quels sont les principaux domaines d\u2019application\u00a0du <\/span><i><span style=\"font-weight: 400;\">NLP<\/span><\/i><span style=\"font-weight: 400;\"> ?<\/span><\/h2><\/li><li style=\"font-weight: 400; font-size: 18px;\"><h2><span style=\"font-weight: 400; font-size: 18px;\">Quelles sont les m\u00e9thodes les plus r\u00e9pandues en <\/span><i><span style=\"font-weight: 400;\">NLP<\/span><\/i><span style=\"font-weight: 400;\">\u00a0?<\/span><\/h2><\/li><\/ul>\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-28a45aa elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"28a45aa\" 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-fe386d4\" data-id=\"fe386d4\" 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-b70aaec elementor-widget elementor-widget-heading\" data-id=\"b70aaec\" 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><h2 class=\"elementor-heading-title elementor-size-default\">Sommaire <\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c2fbfd1 elementor-widget elementor-widget-text-editor\" data-id=\"c2fbfd1\" 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<ol><li><span style=\"text-decoration: underline;\"><span style=\"color: #000000; text-decoration: underline;\"><a style=\"color: #000000; text-decoration: underline;\" href=\"https:\/\/datascientest.com\/introduction-au-nlp-natural-language-processing\">Introduction au NLP<\/a><\/span><\/span><ul><li><span style=\"text-decoration: underline;\"><span style=\"color: #000000; text-decoration: underline;\"><a style=\"color: #000000; text-decoration: underline;\" href=\"#nlp\">D\u00e9finition NLP<\/a><\/span><\/span><\/li><li><span style=\"text-decoration: underline;\"><span style=\"color: #000000; text-decoration: underline;\"><a style=\"color: #000000; text-decoration: underline;\" href=\"#domaines\">Principaux domaines d\u2019application du NLP<\/a><\/span><\/span><\/li><li><span style=\"text-decoration: underline;\"><span style=\"color: #000000; text-decoration: underline;\"><a style=\"color: #000000; text-decoration: underline;\" href=\"#methodes\">M\u00e9thodes les plus r\u00e9pandues en NLP<\/a><\/span><\/span><\/li><li><span style=\"text-decoration: underline;\"><span style=\"color: #000000; text-decoration: underline;\"><a style=\"color: #000000; text-decoration: underline;\" href=\"#perspectives\">Perspectives et enjeux<\/a><\/span><\/span><\/li><\/ul><\/li><li><span style=\"text-decoration: underline;\"><span style=\"color: #000000; text-decoration: underline;\"><a style=\"color: #000000; text-decoration: underline;\" href=\"https:\/\/datascientest.com\/nlp-word-embedding-word2vec\">Word embedding &#8211; Word2vec<\/a><\/span><\/span><\/li><li><span style=\"text-decoration: underline;\"><span style=\"color: #000000; text-decoration: underline;\"><a style=\"color: #000000; text-decoration: underline;\" href=\"https:\/\/datascientest.com\/nlp-word-translation\">NLP &#8211; Word translation<\/a><\/span><\/span><\/li><li><span style=\"text-decoration: underline;\"><span style=\"color: #000000; text-decoration: underline;\"><a style=\"color: #000000; text-decoration: underline;\" href=\"https:\/\/datascientest.com\/nlp-twitter-analyse-de-sentiment\">NLP Twitter &#8211; Analyse des sentiments<\/a><\/span><\/span><\/li><\/ol>\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-053b10a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"053b10a\" 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-428c3f1\" data-id=\"428c3f1\" 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-b64fc64 elementor-widget elementor-widget-menu-anchor\" data-id=\"b64fc64\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\nbody.elementor-page .elementor-widget-menu-anchor{margin-bottom:0}<\/style>\t\t<div id=\"nlp\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6e45346 elementor-widget elementor-widget-heading\" data-id=\"6e45346\" 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\">Qu'est-ce que le NLP ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a2fcc8d elementor-widget elementor-widget-text-editor\" data-id=\"a2fcc8d\" 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 <\/span><b>NLP<\/b><span style=\"font-weight: 400;\"> pour <\/span><b>Natural Language Processing<\/b><span style=\"font-weight: 400;\"> ou <\/span><b>Traitement du Langage<\/b><span style=\"font-weight: 400;\"><strong> Naturel<\/strong> est une discipline qui porte essentiellement sur la <\/span><b>compr\u00e9hension<\/b><span style=\"font-weight: 400;\">, la <\/span><b>manipulation<\/b><span style=\"font-weight: 400;\"> et la <\/span><b>g\u00e9n\u00e9ration<\/b><span style=\"font-weight: 400;\"> du <\/span><b>langage naturel par les machines<\/b><span style=\"font-weight: 400;\">.\u00a0 Ainsi, le <\/span><i><span style=\"font-weight: 400;\">NLP <\/span><\/i><span style=\"font-weight: 400;\">est r\u00e9ellement \u00e0 l\u2019interface entre la science informatique et la linguistique. Il porte donc sur la capacit\u00e9 de la machine \u00e0 interagir directement avec l\u2019humain.<\/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<div class=\"elementor-element elementor-element-97b4d7c e-flex e-con-boxed e-con\" data-id=\"97b4d7c\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-aabac43 e-con-full e-flex e-con\" data-id=\"aabac43\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-db103ea e-con-full e-flex e-con\" data-id=\"db103ea\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2fd19ca elementor-widget elementor-widget-video\" data-id=\"2fd19ca\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/youtu.be\\\/P_bYAOdUQHY&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.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-video .elementor-widget-container{overflow:hidden;transform:translateZ(0)}.elementor-widget-video .elementor-wrapper{aspect-ratio:var(--video-aspect-ratio)}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{height:100%;width:100%;display:flex;border:none;background-color:#000}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-wrapper{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .elementor-open-inline .elementor-custom-embed-image-overlay{position:absolute;top:0;right:0;bottom:0;left:0;background-size:cover;background-position:50%}.elementor-widget-video .elementor-custom-embed-image-overlay{cursor:pointer;text-align:center}.elementor-widget-video .elementor-custom-embed-image-overlay:hover .elementor-custom-embed-play i{opacity:1}.elementor-widget-video .elementor-custom-embed-image-overlay img{display:block;width:100%;aspect-ratio:var(--video-aspect-ratio);-o-object-fit:cover;object-fit:cover;-o-object-position:center center;object-position:center center}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-custom-embed-image-overlay{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-custom-embed-image-overlay img{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .e-hosted-video .elementor-video{-o-object-fit:cover;object-fit:cover}.e-con-inner>.elementor-widget-video,.e-con>.elementor-widget-video{width:var(--container-widget-width);--flex-grow:var(--container-widget-flex-grow)}<\/style>\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-8817ec6 e-con-full e-flex e-con\" data-id=\"8817ec6\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-0fe3b67 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0fe3b67\" 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-8632423\" data-id=\"8632423\" 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-6224a9a elementor-widget elementor-widget-menu-anchor\" data-id=\"6224a9a\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div id=\"domaines\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d31404b elementor-widget elementor-widget-heading\" data-id=\"d31404b\" 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\">\u00c0 quelles probl\u00e9matiques r\u00e9pond le NLP ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cfb4cec elementor-widget elementor-widget-image\" data-id=\"cfb4cec\" 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<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"800\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/NLP_article_5-02-1024x1024.png\" class=\"attachment-large size-large wp-image-6159\" alt=\"NLP\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/NLP_article_5-02-1024x1024.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/NLP_article_5-02-300x300.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/NLP_article_5-02-150x150.png 150w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/NLP_article_5-02-768x768.png 768w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/NLP_article_5-02-1536x1536.png 1536w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/NLP_article_5-02-2048x2048.png 2048w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Domaines d'applications du NLP<\/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<div class=\"elementor-element elementor-element-ae2697f elementor-widget elementor-widget-text-editor\" data-id=\"ae2697f\" 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 NLP est terme assez g\u00e9n\u00e9rique qui recouvre un champ d\u2019application tr\u00e8s vaste. Voici les applications les plus populaires :<\/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-6fa8313 elementor-widget elementor-widget-heading\" data-id=\"6fa8313\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Traduction automatique<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b8f54c4 elementor-widget elementor-widget-text-editor\" data-id=\"b8f54c4\" 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 d\u00e9veloppement\u00a0<strong>d\u2019algorithmes de traduction automatique<\/strong>\u00a0a r\u00e9ellement r\u00e9volutionn\u00e9 la mani\u00e8re dont les textes sont traduits aujourd\u2019hui. Des applications, telles que\u00a0<strong>Google Translator<\/strong>, sont capables de\u00a0<strong>traduire des textes entiers<\/strong>\u00a0sans aucune intervention humaine.<br \/>Le langage naturel \u00e9tant par nature ambigu et variable, ces applications ne reposent pas sur un travail de remplacement mot \u00e0 mot, mais n\u00e9cessitent une v\u00e9ritable analyse et mod\u00e9lisation de texte, connue sous le nom de Traduction automatique statistique (Statistical Machine Translation en anglais).<\/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-59d96af elementor-widget elementor-widget-heading\" data-id=\"59d96af\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Sentiment analysis<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-33e08d5 elementor-widget elementor-widget-text-editor\" data-id=\"33e08d5\" 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>Aussi connue sous le nom de\u00a0<i>\u00ab\u00a0<\/i><b><i>Opinion Mining\u00a0<\/i><\/b><i>\u00bb,\u00a0<\/i>l\u2019<b>analyse des sentiments<\/b>\u00a0consiste \u00e0 identifier les informations subjectives d\u2019un texte pour\u00a0<b>extraire l\u2019opinion de l\u2019auteur<\/b>.\u00a0<\/p><p>\u00c0 titre exemple, lorsqu\u2019une marque lance un nouveau produit, elle peut exploiter les commentaires recueillis sur les r\u00e9seaux sociaux pour identifier le sentiment positif ou n\u00e9gatif globalement partag\u00e9 par les clients.<\/p><p>De mani\u00e8re g\u00e9n\u00e9rale, l\u2019<b>analyse des sentiments<\/b>\u00a0permet de mesurer le niveau de satisfaction des clients vis-\u00e0-vis des produits ou services fournis par une entreprise ou un organisme. Elle peut m\u00eame s\u2019av\u00e9rer\u00a0<b>bien plus efficace que des m\u00e9thodes classiques<\/b>\u00a0comme les sondages.\u00a0<\/p><p>En effet, si l\u2019on rechigne souvent \u00e0 passer du temps \u00e0 compl\u00e9ter de longs questionnaires,\u00a0<b>une partie croissante des consommateurs partage aujourd\u2019hui fr\u00e9quemment leurs opinions sur les r\u00e9seaux sociaux<\/b>. Ainsi, la recherche de textes n\u00e9gatifs et l&rsquo;identification des principales plaintes permettent d&rsquo;am\u00e9liorer les produits, d\u2019adapter la publicit\u00e9 et de r\u00e9duire le niveau d&rsquo;insatisfaction des clients.<\/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-400adae elementor-widget elementor-widget-heading\" data-id=\"400adae\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Marketing<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-59b71a7 elementor-widget elementor-widget-text-editor\" data-id=\"59b71a7\" 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>Les sp\u00e9cialistes du\u00a0<b>marketing<\/b>\u00a0utilisent \u00e9galement le NLP pour rechercher des\u00a0<b>personnes<\/b>\u00a0\u00e9tant\u00a0<b>susceptible d&rsquo;effectuer un achat.<\/b>\u00a0<\/p><p>Ils s\u2019appuient pour cela sur le\u00a0<b>comportement des internautes<\/b>\u00a0sur les sites, les r\u00e9seaux sociaux et les requ\u00eates aux moteurs de recherche.\u00a0<b>C\u2019est gr\u00e2ce \u00e0 ce type d\u2019analyse que Google g\u00e9n\u00e8re un profit non n\u00e9gligeable en proposant la bonne publicit\u00e9 aux bons internautes.\u00a0Chaque fois qu&rsquo;un visiteur clique sur une annonce, l\u2019annonceur reverse jusqu\u2019\u00e0 50 dollars !<\/b><\/p><p>De mani\u00e8re plus g\u00e9n\u00e9rale, les\u00a0<b>m\u00e9thodes de NLP<\/b>\u00a0peuvent \u00eatre exploit\u00e9es pour dresser un portrait riche et complet du march\u00e9 existant, des clients, des probl\u00e8mes, de la concurrence et du potentiel de croissance des nouveaux produits et services de l&rsquo;entreprise.\u00a0<\/p><p>Les sources de donn\u00e9es brutes pour cette analyse comprennent les journaux de ventes, les enqu\u00eates et les m\u00e9dias sociaux&#8230;<\/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-071ee49 elementor-widget elementor-widget-heading\" data-id=\"071ee49\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Chatbots<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9f388db elementor-widget elementor-widget-text-editor\" data-id=\"9f388db\" 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>Les\u00a0<b>m\u00e9thodes NLP<\/b>\u00a0sont au c\u0153ur du fonctionnement des Chatbots actuels. Bien que ces syst\u00e8mes ne soient pas totalement parfaits, ils peuvent aujourd\u2019hui<b>\u00a0facilement g\u00e9rer des t\u00e2ches standards<\/b>\u00a0telles renseigner des clients sur des produits ou services, r\u00e9pondre \u00e0 leurs questions, etc. Ils sont utilis\u00e9s par plusieurs canaux, dont l&rsquo;Internet, les applications et les plateformes de messagerie. L\u2019ouverture de la plateforme\u00a0<b>Facebook Messenger\u00a0<\/b>aux chatbots en 2016 a contribu\u00e9 \u00e0 leur d\u00e9veloppement.<\/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-65bed51 elementor-widget elementor-widget-heading\" data-id=\"65bed51\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Autres domaines d'application<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2a117ae elementor-widget elementor-widget-text-editor\" data-id=\"2a117ae\" 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<ul><li><b>Classification de texte\u00a0:\u00a0<\/b>cela consiste \u00e0\u00a0<b>attribuer un ensemble de cat\u00e9gories pr\u00e9d\u00e9finies \u00e0 un texte donn\u00e9<\/b>. Les classificateurs de texte peuvent \u00eatre utilis\u00e9s pour organiser, structurer et cat\u00e9goriser \u00e0 ensemble de textes.<\/li><li><b>Reconnaissance de caract\u00e8res<\/b>\u00a0:\u00a0 Cela permet d\u2019<b>extraire<\/b>, \u00e0 partir de la reconnaissance des caract\u00e8res, les\u00a0<b>principales informations\u00a0<\/b>des re\u00e7us, des factures, des ch\u00e8ques, des\u00a0<b>documents<\/b>\u00a0de facturation l\u00e9gaux, etc.<\/li><li><b>Correction automatique<\/b>\u00a0: la plupart des \u00e9diteurs de texte sont aujourd\u2019hui muni d\u2019un correcteur orthographique qui permet de\u00a0<b>v\u00e9rifier si le texte contient des fautes d&rsquo;orthographe<\/b>.<\/li><li><b>R\u00e9sum\u00e9 automatique\u00a0:<\/b>\u00a0les\u00a0<b>m\u00e9thodes NLP<\/b>\u00a0sont \u00e9galement utilis\u00e9es pour produire des\u00a0<b>r\u00e9sum\u00e9s courts, pr\u00e9cis et fluides\u00a0<\/b>d&rsquo;un document texte plus long.<\/li><\/ul>\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-6ad6480 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6ad6480\" 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-b56791a\" data-id=\"b56791a\" 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-dd5be5c elementor-widget elementor-widget-menu-anchor\" data-id=\"dd5be5c\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div id=\"methodes\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5ae8af0 elementor-widget elementor-widget-heading\" data-id=\"5ae8af0\" 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\">Quelles sont les principales m\u00e9thodes utilis\u00e9es en NLP ?\n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-603eb27 elementor-widget elementor-widget-text-editor\" data-id=\"603eb27\" 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;\">Globalement, nous pouvons distinguer deux aspects essentiels \u00e0 tout probl\u00e8me de <\/span><i><span style=\"font-weight: 400;\">NLP\u00a0<\/span><\/i><span style=\"font-weight: 400;\">:<\/span><\/p><ul><li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">La <\/span><b>partie \u00ab\u00a0linguistique\u00a0\u00bb<\/b><span style=\"font-weight: 400;\">,\u00a0qui consiste \u00e0 pr\u00e9traiter et transformer les informations en entr\u00e9e en un jeu de donn\u00e9es exploitable.<\/span><\/li><li><span style=\"font-weight: 400;\">La <\/span><b>partie \u00ab\u00a0apprentissage automatique\u00a0\u00bb<\/b><b style=\"font-weight: 400;\"> ou \u00ab\u00a0Data Science\u00a0\u00bb<\/b><span style=\"font-weight: 400;\">, qui porte sur l\u2019application de <\/span><b>mod\u00e8les de\u00a0<i><a href=\"https:\/\/datascientest.com\/category\/machinelearning\" target=\"_blank\" rel=\"noopener\">Machine Learning<\/a> <\/i><\/b><b style=\"font-weight: 400;\">ou<\/b><b> <a href=\"https:\/\/datascientest.com\/category\/deeplearning\" target=\"_blank\" rel=\"noopener\">Deep Learning<\/a><\/b><span style=\"font-weight: 400;\">\u00e0 ce jeu de donn\u00e9es.<\/span><\/li><\/ul>\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-11dd48b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"11dd48b\" 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-1ec83e1\" data-id=\"1ec83e1\" 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-82c5c74 elementor-widget elementor-widget-image\" data-id=\"82c5c74\" 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\t<a href=\"https:\/\/www.peakindicators.com\/blog\/unlocking-insights-from-unstructured-data-with-text-mining%20\">\n\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"450\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/www.peakindicators.png\" class=\"attachment-large size-large wp-image-6006\" alt=\"NLP\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/www.peakindicators.png 822w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/www.peakindicators-300x169.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/www.peakindicators-768x432.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Processus de traitement et mod\u00e9lisation des donn\u00e9es en NLP<\/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<div class=\"elementor-element elementor-element-18252bc elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"18252bc\" 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\/formation-intelligence-artificielle\">\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 notre formation en IA<\/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<section class=\"elementor-section elementor-top-section elementor-element elementor-element-43568ec elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"43568ec\" 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-a4ea25b\" data-id=\"a4ea25b\" 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-6e4b3b3 elementor-widget elementor-widget-text-editor\" data-id=\"6e4b3b3\" 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>Nous allons aborder dans la suite ces deux aspects, en d\u00e9crivant bri\u00e8vement les\u00a0<b>principales m\u00e9thodes<\/b>\u00a0et en mettant en avant les principaux challenges. Nous allons nous appuyer sur un exemple classique\u00a0: la d\u00e9tection de spams.<\/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-df93ac5 elementor-widget elementor-widget-heading\" data-id=\"df93ac5\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">La phase de pr\u00e9traitement : du texte aux donn\u00e9es<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5e27daf elementor-widget elementor-widget-text-editor\" data-id=\"5e27daf\" 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-family: var( --e-global-typography-text-font-family ), Sans-serif;\">Supposons que vous vouliez \u00eatre capable de <\/span><b style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif;\">d\u00e9terminer si un mail est un spam ou non<\/b><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif;\">, uniquement \u00e0 partir de son contenu. \u00c0 cette fin, il est indispensable de <\/span><b style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif;\">transformer les donn\u00e9es brutes<\/b><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif;\"> (le texte du mail) <\/span><b style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif;\">en des donn\u00e9es exploitables<\/b><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif;\">.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Parmi les principales \u00e9tapes, on retrouve\u00a0: <\/span><\/p><ul><li><b>Nettoyage\u00a0: <\/b>Variable selon la source des donn\u00e9es, cette phase consiste \u00e0 r\u00e9aliser des t\u00e2ches telles que la <b>suppression d\u2019urls, d&#8217;emoji<\/b>, etc.<\/li><li><b>Normalisation des donn\u00e9es\u00a0:\u00a0<\/b><ul><li style=\"font-weight: 400;\"><b>Tokenisation<\/b><span style=\"font-weight: 400;\">, ou d\u00e9coupage du texte en plusieurs pi\u00e8ces appel\u00e9s <\/span><i><span style=\"font-weight: 400;\">tokens<\/span><\/i><span style=\"font-weight: 400;\">.\u00a0<\/span><br \/><i>Exemple\u00a0: \u00ab\u00a0Vous trouverez en pi\u00e8ce jointe le document en question\u00a0\u00bb ; \u00ab\u00a0Vous\u00a0\u00bb, \u00ab\u00a0trouverez \u00bb, \u00ab\u00a0en pi\u00e8ce jointe \u00bb, \u00ab le document \u00bb, \u00ab\u00a0en question\u00a0\u00bb.<\/i><\/li><li><b>Stemming\u00a0<\/b>: un m\u00eame mot peut se retrouver sous diff\u00e9rentes formes en fonction du genre (masculin f\u00e9minin), du nombre (singulier, pluriel), la personne (moi, toi, eux&#8230;) etc. Le <b>stemming<\/b> d\u00e9signe g\u00e9n\u00e9ralement le processus heuristique brut qui consiste \u00e0 <b>d\u00e9couper la fin des mots dans afin de ne conserver que la racine du mot<\/b>.<br \/><i>Exemple\u00a0: \u00ab\u00a0trouverez\u00a0\u00bb -&gt; \u00ab\u00a0trouv\u00a0\u00bb<\/i><\/li><li><b style=\"font-weight: 400;\">Lemmatisation\u00a0<\/b><span style=\"font-weight: 400;\">: cela consiste \u00e0 r\u00e9aliser la m\u00eame t\u00e2che mais en utilisant un vocabulaire et une analyse fine de la construction des mots. La <\/span><b>lemmatisation<\/b><span style=\"font-weight: 400;\"> permet donc de supprimer uniquement les terminaisons inflexibles et donc \u00e0<\/span><b> isoler la forme canonique du mot<\/b><span style=\"font-weight: 400;\">, connue sous le nom de lemme.\u00a0<\/span><i style=\"font-weight: 400;\">Exemple : \u00ab trouvez \u00bb -&gt; trouver<\/i><\/li><li style=\"font-weight: 400;\"><b>Autres op\u00e9rations\u00a0:<\/b><span style=\"font-weight: 400;\"> suppression des chiffres, ponctuation, symboles et <\/span><i><span style=\"font-weight: 400;\">stopwords<\/span><\/i><span style=\"font-weight: 400;\">, passage en minuscule.<\/span><\/li><\/ul><\/li><\/ul><p>Afin de pouvoir appliquer les <b>m\u00e9thodes de Machine Learning <\/b>aux probl\u00e8mes relatifs au langage naturel, il est indispensable de <b>transformer les donn\u00e9es textuelles en donn\u00e9es num\u00e9riques<\/b>.<br \/>Il existe plusieurs approches dont les principales sont les suivantes :<\/p><ul><li><b><i>Term-Frequency (TF)<\/i><\/b><b>\u00a0:<\/b><span style=\"font-weight: 400;\"> cette m\u00e9thode consiste \u00e0 compter le nombre d&rsquo;occurrences des <\/span><i><span style=\"font-weight: 400;\">tokens<\/span><\/i><span style=\"font-weight: 400;\"> pr\u00e9sents dans le corpus pour chaque texte. Chaque texte est alors repr\u00e9sent\u00e9 par un <\/span><b>vecteur d&rsquo;occurrences<\/b><span style=\"font-weight: 400;\">. On parle g\u00e9n\u00e9ralement de <\/span><i><b>Bag-Of-Word<\/b><\/i><span style=\"font-weight: 400;\">, ou sac de mots en fran\u00e7ais. <\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-97952d0 elementor-widget elementor-widget-image\" data-id=\"97952d0\" 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\t<a href=\"https:\/\/www.analyticsvidhya.com\/blog\/2017\/06\/word-embeddings-count-word2veec\/\">\n\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"715\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/Capture-d\u2019e\u0301cran-2020-07-19-a\u0300-11.17.46.png\" class=\"attachment-large size-large wp-image-6008\" alt=\"NLP\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/Capture-d\u2019e\u0301cran-2020-07-19-a\u0300-11.17.46.png 808w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/Capture-d\u2019e\u0301cran-2020-07-19-a\u0300-11.17.46-300x268.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/Capture-d\u2019e\u0301cran-2020-07-19-a\u0300-11.17.46-768x686.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Repr\u00e9sentation des vecteurs issues de la m\u00e9thode Term-Frequency (TF)<\/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<div class=\"elementor-element elementor-element-1cb58f7 elementor-widget elementor-widget-text-editor\" data-id=\"1cb58f7\" 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;\">N\u00e9anmoins, cette approche pr\u00e9sente un inconv\u00e9nient majeur\u00a0: certains mots sont par nature plus utilis\u00e9s que d\u2019autres, ce qui <\/span><b>peut conduire le mod\u00e8le \u00e0 des r\u00e9sultats erron\u00e9s<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><ul><li><b style=\"font-weight: 400;\"><i>Term Frequency-Inverse Document Frequency (TF-IDF)<\/i><\/b><span style=\"font-weight: 400;\"> : cette m\u00e9thode consiste \u00e0 <\/span><b>compter le nombre d&rsquo;occurrences des <i>tokens<\/i><\/b><span style=\"font-weight: 400;\"> pr\u00e9sents dans le corpus pour chaque texte, que l\u2019on divise ensuite par le nombre d\u2019occurrences total de ces m\u00eame <\/span><i style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">tokens<\/span><\/i><span style=\"font-weight: 400;\"> dans tout le corpus.<\/span><\/li><\/ul><p>Pour le terme x pr\u00e9sent dans le document y, on peut d\u00e9finir son poids par la relation suivante :<\/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-c8e36e8 elementor-widget elementor-widget-image\" data-id=\"c8e36e8\" 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=\"248\" height=\"56\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/07\/Capture-d\u2019e\u0301cran-2020-07-19-a\u0300-10.53.53.png\" class=\"attachment-large size-large wp-image-6010\" alt=\"NLP formule\" \/>\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-a75a56e elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a75a56e\" 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-e0c04e0\" data-id=\"e0c04e0\" 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-f30556e elementor-widget elementor-widget-text-editor\" data-id=\"f30556e\" 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;\">O\u00f9&nbsp;:<\/span><\/p>\n<ul>\n<li>t\u0192<sub>x,y<\/sub> est la fr\u00e9quence du terme x dans y ;<\/li>\n<li>d\u0192<sub>x <\/sub> est le nombre de documents contenant x ;<\/li>\n<li>N est le total de documents.<\/li>\n<\/ul>\n<blockquote>\n<p>Cette approche permet donc d\u2019obtenir pour chaque texte une repr\u00e9sentation vectorielle qui comporte des vecteurs de poids et non plus d&rsquo;occurrences.<\/p>\n<\/blockquote>\n<p>L\u2019efficacit\u00e9 de ces m\u00e9thodes diff\u00e8re selon le cas d\u2019application. Toutefois, elles pr\u00e9sentent deux principales limites :<\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Plus le vocabulaire du corpus est riche, plus la <\/span><b>taille des vecteurs est grande<\/b><span style=\"font-weight: 400;\">, ce qui peut repr\u00e9senter un <\/span><b>probl\u00e8me pour les mod\u00e8les d\u2019apprentissage<\/b><span style=\"font-weight: 400;\"> utilis\u00e9es dans l\u2019\u00e9tape suivante.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Le comptage d\u2019occurrence des mots <\/span><b>ne permet pas de rendre compte<\/b><span style=\"font-weight: 400;\"> de leur agencement et donc du<\/span><b> sens des phrases<\/b><span style=\"font-weight: 400;\">.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Il existe une autre approche qui permet de <\/span><b>rem\u00e9dier \u00e0 ces probl\u00e8mes<\/b><span style=\"font-weight: 400;\">&nbsp;<\/span><i><span style=\"font-weight: 400;\">:&nbsp; Word Embedding.<\/span><\/i><span style=\"font-weight: 400;\"> Elle consiste \u00e0 construire des vecteurs de taille fixe qui <\/span><b>prennent en compte le contexte dans lequel se trouvent les mots<\/b><span style=\"font-weight: 400;\">.&nbsp;<\/span><\/p>\n<blockquote>\n<p><span style=\"font-weight: 400;\">Ainsi, deux mots pr\u00e9sents dans des contextes similaires auront des vecteurs plus proches (en terme de distance vectorielle). Cela permet alors de capturer \u00e0 la fois similarit\u00e9s s\u00e9mantiques, syntaxiques ou th\u00e9matiques des mots.<\/span><\/p>\n<\/blockquote>\n<p><span style=\"font-weight: 400;\">Une description plus d\u00e9taill\u00e9e de cette m\u00e9thode fera l\u2019objet d\u2019une prochaine section.<\/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-c9e8cfe elementor-widget elementor-widget-heading\" data-id=\"c9e8cfe\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">La phase d'apprentissage : des donn\u00e9es au mod\u00e8le<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6cd0e32 elementor-widget elementor-widget-text-editor\" data-id=\"6cd0e32\" 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;\">De mani\u00e8re globale, on peut distinguer <\/span><b>3 principales approches NLP\u00a0<\/b><span style=\"font-weight: 400;\">: les <\/span><b>m\u00e9thodes bas\u00e9es sur des r\u00e8gles<\/b><span style=\"font-weight: 400;\">, mod\u00e8les classiques de <\/span><i><b>Machine Learning <\/b><\/i><span style=\"font-weight: 400;\">et mod\u00e8les de<\/span><b> <\/b><i><b>Deep Learning<\/b><span style=\"font-weight: 400;\">.<\/span><\/i><\/p><ul><li><strong>M\u00e9thodes bas\u00e9es sur des r\u00e8gles :\u00a0<\/strong>Les m\u00e9thodes fond\u00e9es sur des r\u00e8gles reposent en grande partie sur l&rsquo;<b style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">\u00e9laboration de r\u00e8gles sp\u00e9cifiques \u00e0 un domaine <\/b><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">(par exemple, les expressions r\u00e9guli\u00e8res). Elles peuvent \u00eatre utilis\u00e9es pour r\u00e9soudre des probl\u00e8mes simples tels que l&rsquo;extraction de donn\u00e9es structur\u00e9es \u00e0 partir de donn\u00e9es non structur\u00e9es (par exemple, les pages web).<br \/><\/span>Dans le cas de la <b style=\"background-color: transparent; font-size: var( --e-global-typography-text-font-size ); font-family: var( --e-global-typography-text-font-family ), Sans-serif;\">d\u00e9tection de spams<\/b><span style=\"background-color: transparent; font-size: var( --e-global-typography-text-font-size ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-weight: var( --e-global-typography-text-font-weight );\">, cela pourrait consister \u00e0 consid\u00e9rer comme <\/span><b style=\"background-color: transparent; font-size: var( --e-global-typography-text-font-size ); font-family: var( --e-global-typography-text-font-family ), Sans-serif;\">e-mails ind\u00e9sirables<\/b><span style=\"background-color: transparent; font-size: var( --e-global-typography-text-font-size ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-weight: var( --e-global-typography-text-font-weight );\">, ceux qui comportent des<\/span><b style=\"background-color: transparent; font-size: var( --e-global-typography-text-font-size ); font-family: var( --e-global-typography-text-font-family ), Sans-serif;\"> buzz words<\/b><span style=\"background-color: transparent; font-size: var( --e-global-typography-text-font-size ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-weight: var( --e-global-typography-text-font-weight );\"> tels que\u00a0\u00ab\u00a0promotion\u00a0\u00bb, \u00ab\u00a0offre limit\u00e9e\u00a0\u00bb, etc.<br \/><\/span>N\u00e9anmoins, ces m\u00e9thodes simples peuvent \u00eatre rapidement d\u00e9pass\u00e9es par la complexit\u00e9 du langage naturel et s\u2019av\u00e9rer \u00eatre inefficace.<br \/><br \/><\/li><\/ul><ul><li><strong>Mod\u00e8les classiques de Machine Learning :\u00a0<\/strong>Les approches classiques d&rsquo;apprentissage automatique peuvent \u00eatre utilis\u00e9es pour r\u00e9soudre des probl\u00e8mes plus difficiles. Contrairement aux m\u00e9thodes fond\u00e9es sur des r\u00e8gles pr\u00e9d\u00e9finies, elles reposent sur des<b style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\"> m\u00e9thodes qui portent r\u00e9ellement sur la compr\u00e9hension du langage<\/b><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">. Elles exploitent les donn\u00e9es obtenues \u00e0 partir des textes bruts pr\u00e9trait\u00e9s via une des m\u00e9thodes d\u00e9crites en haut par exemple. Elles peuvent \u00e9galement utiliser des donn\u00e9es relatives \u00e0 la longueur des phrases, \u00e0 l&rsquo;occurrence de mots sp\u00e9cifiques, etc. Elles mettent g\u00e9n\u00e9ralement en \u0153uvre un <\/span><b style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">mod\u00e8le statistique d&rsquo;apprentissage automatique <\/b><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">tels que ceux de <\/span><b style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">Naive Bayes<\/b><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">, de <\/span><b style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">R\u00e9gression Logistique<\/b><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">, etc.<br \/><br \/><\/span><\/li><\/ul><ul><li><b>Mod\u00e8les de Deep Learning :<\/b>L\u2019utilisation de mod\u00e8les d\u2019apprentissage en profondeur pour les probl\u00e9matiques NLP fait l\u2019objet de nombreuses recherches actuellement.\u00a0<\/li><\/ul><p><span style=\"font-weight: 400;\"><br \/>Ces mod\u00e8les se g\u00e9n\u00e9ralisent encore mieux que les approches classiques d&rsquo;apprentissage car ils n\u00e9cessitent une <\/span><b>phase de pr\u00e9traitement du texte moins sophistiqu\u00e9e\u00a0<\/b><span style=\"font-weight: 400;\">: les c<\/span><b>ouches de neurones<\/b><span style=\"font-weight: 400;\"> peuvent \u00eatre per\u00e7ues comme des <\/span><b>extracteurs automatiques de <i>features<\/i><\/b>.<\/p><p><span style=\"font-weight: 400;\">Cela permet alors de construire des mod\u00e8les de bout en bout avec peu de pr\u00e9traitement des donn\u00e9es. En dehors de la partie <i>feature engineering<\/i>, les<b> capacit\u00e9s d&rsquo;apprentissage des algorithmes de <\/b><b><i>Deep Learning<\/i><\/b><b> sont g\u00e9n\u00e9ralement plus puissantes que celles de <\/b><b><i>Machine Learning <\/i><\/b><b>classique<\/b>, ce qui permet d&rsquo;<b>obtenir de meilleurs scores sur diff\u00e9rentes t\u00e2ches complexes de NLP <\/b>dures telles que la traduction.\u00a0<\/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<div class=\"elementor-element elementor-element-e45948f e-flex e-con-boxed e-con\" data-id=\"e45948f\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-61791ee e-con-full e-flex e-con\" data-id=\"61791ee\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9979759 e-con-full e-flex e-con\" data-id=\"9979759\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2a260c3 elementor-widget elementor-widget-video\" data-id=\"2a260c3\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/www.youtube.com\\\/watch?v=DazUaVu5MO0&amp;ab_channel=DataScientest&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-b7d306c e-con-full e-flex e-con\" data-id=\"b7d306c\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-7b387e8 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7b387e8\" 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-c00cdbd\" data-id=\"c00cdbd\" 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-c0d8f79 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"c0d8f79\" 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\/formation-intelligence-artificielle\">\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\">Apprendre \u00e0 utiliser des mod\u00e8les de Machine Learning<\/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<section class=\"elementor-section elementor-top-section elementor-element elementor-element-98b837f elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"98b837f\" 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-7534510\" data-id=\"7534510\" 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-46245aa elementor-widget elementor-widget-menu-anchor\" data-id=\"46245aa\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div id=\"perspectives\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bfd3503 elementor-widget elementor-widget-heading\" data-id=\"bfd3503\" 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\">Quels sont les perspectives et enjeux du NLP ?\n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1f86986 elementor-widget elementor-widget-text-editor\" data-id=\"1f86986\" 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>Les r\u00e8gles qui r\u00e9gissent la transformation de texte en langage naturel en information ne sont pas faciles \u00e0 comprendre pour les ordinateurs.\u00a0Cela n\u00e9cessite de comprendre \u00e0 la fois les mots et la fa\u00e7on dont les concepts sont li\u00e9s pour d\u00e9livrer le message voulu. Parmi les principaux challenges\u00a0:\u00a0<\/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-bc764d5 elementor-widget elementor-widget-heading\" data-id=\"bc764d5\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Ambigu\u00eft\u00e9<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b84e19b elementor-widget elementor-widget-text-editor\" data-id=\"b84e19b\" 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>En langage naturel,\u00a0<b>les mots sont uniques mais peuvent avoir des significations diff\u00e9rentes<\/b>\u00a0selon le contexte, ce qui entra\u00eene une ambigu\u00eft\u00e9 au niveau lexical, syntaxique et s\u00e9mantique. Pour r\u00e9soudre ce probl\u00e8me, le NPL propose plusieurs m\u00e9thodes, telles que l&rsquo;<b>\u00e9valuation du contexte\u00a0<\/b>par exemple. Cependant, la compr\u00e9hension de la signification s\u00e9mantique des mots d&rsquo;une phrase reste une t\u00e2che en cours de recherche.<\/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-89c4667 elementor-widget elementor-widget-heading\" data-id=\"89c4667\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Synonymie<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4f919fb elementor-widget elementor-widget-text-editor\" data-id=\"4f919fb\" 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>Un autre ph\u00e9nom\u00e8ne cl\u00e9 en langage naturel est le fait que nous pouvons\u00a0<b>exprimer la m\u00eame id\u00e9e avec diff\u00e9rents termes<\/b>\u00a0qui d\u00e9pendent \u00e9galement du contexte sp\u00e9cifique.\u00a0<\/p><p><i>Par exemple, les termes \u00ab\u00a0grand\u00a0\u00bb et \u00ab\u00a0large\u00a0\u00bb peuvent \u00eatre synonymes pour d\u00e9crire un objet ou un b\u00e2timent, mais ils ne sont pas interchangeables dans tous les contextes\u00a0:\u00a0 \u00ab\u00a0grand\u00a0\u00bb peut signifier plus \u00e2g\u00e9.<\/i><\/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-531a0c9 elementor-widget elementor-widget-heading\" data-id=\"531a0c9\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Cor\u00e9f\u00e9rence<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-251b446 elementor-widget elementor-widget-text-editor\" data-id=\"251b446\" 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>Les t\u00e2ches de cor\u00e9f\u00e9rence consistent \u00e0\u00a0<b>trouver toutes les expressions qui se r\u00e9f\u00e8rent \u00e0 la m\u00eame entit\u00e9<\/b>. Il s&rsquo;agit d&rsquo;une \u00e9tape importante pour de\u00a0<b>nombreuses t\u00e2ches de NLP<\/b>\u00a0de haut niveau qui impliquent une\u00a0<b>compr\u00e9hension du texte dans sa globalit\u00e9<\/b>, telles que le r\u00e9sum\u00e9 de documents, la r\u00e9ponse \u00e0 des questions et l&rsquo;extraction d&rsquo;informations. Ce probl\u00e8me a connu un renouveau avec l&rsquo;introduction de<b>\u00a0techniques de pointe de\u00a0<i>Deep Learning<\/i>\u00a0<\/b>.<\/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-a7ea288 elementor-widget elementor-widget-heading\" data-id=\"a7ea288\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Style d'\u00e9criture<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0070d7f elementor-widget elementor-widget-text-editor\" data-id=\"0070d7f\" 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;\">Selon la personnalit\u00e9 de l&rsquo;auteur, ses intentions et \u00e9motions, une m\u00eame id\u00e9e peut \u00eatre exprim\u00e9e de diverses mani\u00e8res.\u00a0<\/span><span style=\"font-weight: 400;\">Certains auteurs n\u2019h\u00e9sitent pas \u00e0 utiliser de l&rsquo;<\/span><b>ironie<\/b><span style=\"font-weight: 400;\"> ou le <\/span><b>sarcasme<\/b><span style=\"font-weight: 400;\"> et donc v\u00e9hiculer un <\/span><b>sens oppos\u00e9 au sens litt\u00e9ral<\/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<div class=\"elementor-element elementor-element-5738946 elementor-widget elementor-widget-text-editor\" data-id=\"5738946\" 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;\">Ainsi, alors que les humains peuvent facilement ma\u00eetriser une langue, l&rsquo;ambigu\u00eft\u00e9 et les caract\u00e9ristiques impr\u00e9cises des langues naturelles sont ce qui rend la NLP difficile \u00e0 mettre en \u0153uvre pour les machines.<\/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-f37c2fc elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f37c2fc\" 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-9a48d50\" data-id=\"9a48d50\" 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-ac8f3b9 elementor-widget elementor-widget-text-editor\" data-id=\"ac8f3b9\" 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>Vous souhaitez passer ma\u00eetre dans l&rsquo;art du NLP ? La suite de notre dossier arrive vite ! Au programme du prochain \u00e9pisode : comment repr\u00e9senter un mot par un vecteur gr\u00e2ce au <a href=\"https:\/\/datascientest.com\/le-word-embedding\">Word Embedding<\/a> ?\u00a0<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-2e0538e e-flex e-con-boxed e-con\" data-id=\"2e0538e\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-f672def e-con-full e-flex e-con\" data-id=\"f672def\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-3f6d99c e-con-full e-flex e-con\" data-id=\"3f6d99c\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a3e800d elementor-widget elementor-widget-video\" data-id=\"a3e800d\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/www.youtube.com\\\/watch?v=mGHZohCf11A&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4962fba elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"4962fba\" 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\/formation-intelligence-artificielle\">\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 notre formation en IA<\/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<\/div>\n\t\t<div class=\"elementor-element elementor-element-bd0c54a e-con-full e-flex e-con\" data-id=\"bd0c54a\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<\/div>\n\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-3c5f84d elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3c5f84d\" 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-bcf9c25\" data-id=\"bcf9c25\" 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-9b5caee elementor-widget elementor-widget-text-editor\" data-id=\"9b5caee\" 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;\"><b>R\u00e9f\u00e9rences:<\/b><\/span><\/em><\/p><p><em><span style=\"color: #000000;\">P. Olivier, Introduction au NLP (Partie I), Ekino<\/span><\/em><\/p><p><em><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/www.ekino.fr\/articles\/introduction-au-nlp-partie-ii\">P. Olivier, Introduction au NLP (Partie II), Ekino<\/a><\/span><\/em><\/p><p><em><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/towardsdatascience.com\/introduction-to-natural-language-processing-nlp-323cc007df3d\">I. ElDen, Introduction to Natural Language Processing (NLP), Towards Data Science, September 2017<\/a><\/span><\/em><\/p><p><em><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/towardsdatascience.com\/natural-language-processing-nlp-top-10-applications-to-know-b2c80bd428cb\">O. Kharkovyna, Natural Language Processing (NLP): Top 10 Applications to Know, Towards Data Science, December 2019<\/a><\/span><\/em><\/p><p><em><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/medium.com\/sciforce\/biggest-open-problems-in-natural-language-processing-7eb101ccfc9\">Sciforce, Biggest Open Problems in Natural Language Processing, February 2020<\/a><\/span><\/em><\/p><p><em><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/www.analyticsvidhya.com\/blog\/2017\/06\/word-embeddings-count-word2veec\/\">An Intuitive Understanding of Word Embeddings: From Count Vectors to Word2Vec, Analytics Vidhya, June 2017<\/a><\/span><\/em><\/p><p><em><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"http:\/\/www.datascience.manchester.ac.uk\/research\/methodologies\/natural-language-processing-nlp-text-mining\/\">S. Ananiadou, J. McNaught, The Natural Language Processing and Text Mining, University of Manchester<\/a><\/span><\/em><\/p><p><em><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/www.peakindicators.com\/blog\/unlocking-insights-from-unstructured-data-with-text-mining\">P. Clough and F. Borg, Unlocking Insights from Unstructured Data with Text Mining, December 2019<\/a><\/span><\/em><\/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<div class=\"elementor-element elementor-element-ace3a34 e-flex e-con-boxed e-con\" data-id=\"ace3a34\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1d0241a elementor-widget elementor-widget-html\" data-id=\"1d0241a\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [{\n    \"@type\": \"Question\",\n    \"name\": \"Qu'est-ce que le NLP ?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"Le NLP pour Natural Language Processing ou Traitement du Langage Naturel est une discipline qui porte essentiellement sur la compr\u00e9hension, la manipulation et la g\u00e9n\u00e9ration du langage naturel par les machines.\u00a0 Ainsi, le NLP est r\u00e9ellement \u00e0 l\u2019interface entre la science informatique et la linguistique. Il porte donc sur la capacit\u00e9 de la machine \u00e0 interagir directement avec l\u2019humain.\"\n    }\n  },{\n    \"@type\": \"Question\",\n    \"name\": \"\u00c0 quelles probl\u00e9matiques r\u00e9pond le NLP ?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"Le NLP est terme assez g\u00e9n\u00e9rique qui recouvre un champ d\u2019application tr\u00e8s vaste.\"\n    }\n  },{\n    \"@type\": \"Question\",\n    \"name\": \"Quels sont les perspectives et enjeux du NLP ?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"Les r\u00e8gles qui r\u00e9gissent la transformation de texte en langage naturel en information ne sont pas faciles \u00e0 comprendre pour les ordinateurs.\u00a0Cela n\u00e9cessite de comprendre \u00e0 la fois les mots et la fa\u00e7on dont les concepts sont li\u00e9s pour d\u00e9livrer le message voulu.\"\n    }\n  }]\n}\n<\/script>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Vous \u00eates-vous d\u00e9j\u00e0 demand\u00e9 comment des assistants personnels IA tels que Siri ou Cortana fonctionnent ? Comment votre correcteur d\u2019orthographe a \u00e9t\u00e9 capable de d\u00e9tecter des erreurs de syntaxe que vous-m\u00eame n\u2019auriez pas rep\u00e9r\u00e9es ? Comment votre moteur de recherche r\u00e9ussit \u00e0 deviner les mots que vous \u00e9tiez sur le point d\u2019\u00e9crire d\u00e8s les premi\u00e8res [&hellip;]<\/p>\n","protected":false},"author":78,"featured_media":185609,"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>Natural Language Processing (NLP) : D\u00e9finition et principes<\/title>\n<meta name=\"description\" content=\"D\u00e9couvrez la d\u00e9finition du NLP - Natural Language Processing ainsi que ses applications. 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