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<oembed><version>1.0</version><provider_name>Microsoft Research</provider_name><provider_url>https://www.microsoft.com/en-us/research</provider_url><author_name>Eric Horvitz</author_name><author_url>https://www.microsoft.com/en-us/research/people/horvitz/</author_url><title>Analyzing and Predicting Task Reminders - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="cs5rWiVNg7"&gt;&lt;a href="https://www.microsoft.com/en-us/research/publication/analyzing-predicting-task-reminders/"&gt;Analyzing and Predicting Task Reminders&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/analyzing-predicting-task-reminders/embed/#?secret=cs5rWiVNg7" width="600" height="338" title="&#x201C;Analyzing and Predicting Task Reminders&#x201D; &#x2014; Microsoft Research" data-secret="cs5rWiVNg7" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><description>Automated personal assistants such as Siri, Cortana, and Google Now provide services to help users accomplish tasks, including tools to set reminders. We study how people specify and use reminders. Our study analyzes a sample of six months of logs of userspecified reminders from Cortana (Microsoft&#x2019;s intelligent personal assistant), the first large-scale analysis of such [&hellip;]</description></oembed>
