{"id":182671,"date":"2008-02-28T00:00:00","date_gmt":"2009-10-31T09:53:22","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/modeling-intention-in-email-speech-acts-information-leaks-and-user-ranking-methods\/"},"modified":"2016-09-09T10:01:43","modified_gmt":"2016-09-09T17:01:43","slug":"modeling-intention-in-email-speech-acts-information-leaks-and-user-ranking-methods","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/modeling-intention-in-email-speech-acts-information-leaks-and-user-ranking-methods\/","title":{"rendered":"Modeling Intention in Email: Speech Acts, Information Leaks and User Ranking Methods"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Email management has a fundamental role in work productivity. In this talk I will present evidence that machine learning techniques can be effectively used to improve email management by modeling different aspects of user intention. First I&#8217;ll propose a taxonomy of Speech Acts applied to email communication, or &#8220;email acts&#8221;, and show that email act classification can be largely automated, potentially leading to better email prioritization and management. Then I&#8217;ll describe how machine learning can be used to reduce the chances of high-cost email addressing errors. One type of high-cost error is an &#8220;email leak&#8221; , i.e., mistakenly sending a sensitive email message to the wrong recipient. Another type of addressing error is forgetting to add an important collaborator as recipient, a likely source of costly misunderstandings and communication delays. I&#8217;ll present different approaches to these problems, including solutions based on rank aggregation and new (re)ranking techniques.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Email management has a fundamental role in work productivity. In this talk I will present evidence that machine learning techniques can be effectively used to improve email management by modeling different aspects of user intention. First I&#8217;ll propose a taxonomy of Speech Acts applied to email communication, or &#8220;email acts&#8221;, and show that email act [&hellip;]<\/p>\n","protected":false},"featured_media":194727,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_hide_image_in_river":0,"footnotes":""},"research-area":[],"msr-video-type":[],"msr-locale":[268875],"msr-post-option":[],"msr-session-type":[],"msr-impact-theme":[],"msr-pillar":[],"msr-episode":[],"msr-research-theme":[],"class_list":["post-182671","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/z7-Fi3-lppc","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/182671","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":0,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/182671\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/194727"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=182671"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=182671"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=182671"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=182671"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=182671"},{"taxonomy":"msr-session-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-session-type?post=182671"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=182671"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=182671"},{"taxonomy":"msr-episode","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-episode?post=182671"},{"taxonomy":"msr-research-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-theme?post=182671"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}