{"version":"1.0","provider_name":"Microsoft Research","provider_url":"https:\/\/www.microsoft.com\/en-us\/research","author_name":"Chin-Yew Lin","author_url":"https:\/\/www.microsoft.com\/en-us\/research\/people\/cyl\/","title":"Data2Text: Automated Text Generation from Structured Data - Microsoft Research","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"AkkUD4yEmt\"><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/project\/data2text-automated-text-generation-from-structured-data\/\">Data2Text: Automated Text Generation from Structured Data<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/project\/data2text-automated-text-generation-from-structured-data\/embed\/#?secret=AkkUD4yEmt\" width=\"600\" height=\"338\" title=\"&#8220;Data2Text: Automated Text Generation from Structured Data&#8221; &#8212; Microsoft Research\" data-secret=\"AkkUD4yEmt\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/* ]]> *\/\n<\/script>\n","description":"The Data2Text project aims to automatically generate fluent and fact-based descriptions or utterances given a data table. Typical business applications for text generation include the generation of financial and sports news stories, the generation of product descriptions, the analysis and interpretation of business data, and the analysis and interpretation of Internet of Things data, etc. Figure 1 gives an example of the automatic generation of weather forecasts. Figure 1a is a structured weather data collected by various sensors, the machine will be figure 1a data as input, output figure 1b weather forecast.","thumbnail_url":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2021\/01\/D2T-ProductDescription.png"}