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	<id>https://wiki.umiacs.umd.edu/clip/index.php?action=history&amp;feed=atom&amp;title=HumAssist</id>
	<title>HumAssist - Revision history</title>
	<link rel="self" type="application/atom+xml" href="https://wiki.umiacs.umd.edu/clip/index.php?action=history&amp;feed=atom&amp;title=HumAssist"/>
	<link rel="alternate" type="text/html" href="https://wiki.umiacs.umd.edu/clip/index.php?title=HumAssist&amp;action=history"/>
	<updated>2026-04-18T08:27:12Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
	<generator>MediaWiki 1.43.7</generator>
	<entry>
		<id>https://wiki.umiacs.umd.edu/clip/index.php?title=HumAssist&amp;diff=957&amp;oldid=prev</id>
		<title>Resnik at 15:58, 10 December 2017</title>
		<link rel="alternate" type="text/html" href="https://wiki.umiacs.umd.edu/clip/index.php?title=HumAssist&amp;diff=957&amp;oldid=prev"/>
		<updated>2017-12-10T15:58:50Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;table style=&quot;background-color: #fff; color: #202122;&quot; data-mw=&quot;interface&quot;&gt;
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				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;Revision as of 15:58, 10 December 2017&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l1&quot;&gt;Line 1:&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;Line 1:&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-side-deleted&quot;&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;+&quot;&gt;&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-side-deleted&quot;&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;+&quot;&gt;&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&#039;&#039;&#039;Identifying Humanitarian Assistance Needs in Low Resource Languages&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-side-deleted&quot;&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;+&quot;&gt;&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&#039;&#039;&#039;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-side-deleted&quot;&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;+&quot;&gt;&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;DARPA&amp;#039;s Low Resource Languages for Emergent Incidents  (LORELEI) program [https://www.darpa.mil/program/low-resource-languages-for-emergent-incidents]&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;DARPA&amp;#039;s Low Resource Languages for Emergent Incidents  (LORELEI) program [https://www.darpa.mil/program/low-resource-languages-for-emergent-incidents]&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;is focused  on enabling  low-cost development of capabilities for low-resource languages, targeted at humanitarian assistance and disaster relief ([https://health.mil/Military-Health-Topics/Health-Readiness/Global-Health-Engagement/Humanitarian-Assistance-and-Disaster-Relief HADR]) in the aftermath of a crisis like an earthquake, tsunami, or epidemic.  In this project we are developing new technologies for quickly ramping up the ability to extract actionable information from online sources related to both population needs (e.g. food or water shortages, lack of shelter, need for medical assistance) and population mental state (e.g. fear, anger).  Methodologically we are focused on advanced topic models and combinations of topic models with deep learning methods.&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;is focused  on enabling  low-cost development of capabilities for low-resource languages, targeted at humanitarian assistance and disaster relief ([https://health.mil/Military-Health-Topics/Health-Readiness/Global-Health-Engagement/Humanitarian-Assistance-and-Disaster-Relief HADR]) in the aftermath of a crisis like an earthquake, tsunami, or epidemic.  In this project we are developing new technologies for quickly ramping up the ability to extract actionable information from online sources related to both population needs (e.g. food or water shortages, lack of shelter, need for medical assistance) and population mental state (e.g. fear, anger).  Methodologically we are focused on advanced topic models and combinations of topic models with deep learning methods.&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>Resnik</name></author>
	</entry>
	<entry>
		<id>https://wiki.umiacs.umd.edu/clip/index.php?title=HumAssist&amp;diff=941&amp;oldid=prev</id>
		<title>Louiqa at 05:20, 8 December 2017</title>
		<link rel="alternate" type="text/html" href="https://wiki.umiacs.umd.edu/clip/index.php?title=HumAssist&amp;diff=941&amp;oldid=prev"/>
		<updated>2017-12-08T05:20:36Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;table style=&quot;background-color: #fff; color: #202122;&quot; data-mw=&quot;interface&quot;&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;tr class=&quot;diff-title&quot; lang=&quot;en&quot;&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;Revision as of 05:20, 8 December 2017&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l1&quot;&gt;Line 1:&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;Line 1:&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;−&quot;&gt;&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;DARPA&#039;s Low Resource Languages for Emergent Incidents  (LORELEI)&lt;del style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;] &lt;/del&gt;program [https://www.darpa.mil/program/low-resource-languages-for-emergent-incidents]&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;+&quot;&gt;&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;DARPA&#039;s Low Resource Languages for Emergent Incidents  (LORELEI) program [https://www.darpa.mil/program/low-resource-languages-for-emergent-incidents]&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;is focused  on enabling  low-cost development of capabilities for low-resource languages, targeted at humanitarian assistance and disaster relief ([https://health.mil/Military-Health-Topics/Health-Readiness/Global-Health-Engagement/Humanitarian-Assistance-and-Disaster-Relief HADR]) in the aftermath of a crisis like an earthquake, tsunami, or epidemic.  In this project we are developing new technologies for quickly ramping up the ability to extract actionable information from online sources related to both population needs (e.g. food or water shortages, lack of shelter, need for medical assistance) and population mental state (e.g. fear, anger).  Methodologically we are focused on advanced topic models and combinations of topic models with deep learning methods.&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;is focused  on enabling  low-cost development of capabilities for low-resource languages, targeted at humanitarian assistance and disaster relief ([https://health.mil/Military-Health-Topics/Health-Readiness/Global-Health-Engagement/Humanitarian-Assistance-and-Disaster-Relief HADR]) in the aftermath of a crisis like an earthquake, tsunami, or epidemic.  In this project we are developing new technologies for quickly ramping up the ability to extract actionable information from online sources related to both population needs (e.g. food or water shortages, lack of shelter, need for medical assistance) and population mental state (e.g. fear, anger).  Methodologically we are focused on advanced topic models and combinations of topic models with deep learning methods.&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>Louiqa</name></author>
	</entry>
	<entry>
		<id>https://wiki.umiacs.umd.edu/clip/index.php?title=HumAssist&amp;diff=940&amp;oldid=prev</id>
		<title>Louiqa at 05:20, 8 December 2017</title>
		<link rel="alternate" type="text/html" href="https://wiki.umiacs.umd.edu/clip/index.php?title=HumAssist&amp;diff=940&amp;oldid=prev"/>
		<updated>2017-12-08T05:20:11Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;table style=&quot;background-color: #fff; color: #202122;&quot; data-mw=&quot;interface&quot;&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;tr class=&quot;diff-title&quot; lang=&quot;en&quot;&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;Revision as of 05:20, 8 December 2017&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l1&quot;&gt;Line 1:&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;Line 1:&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;DARPA&amp;#039;s Low Resource Languages for Emergent Incidents  (LORELEI)] program [https://www.darpa.mil/program/low-resource-languages-for-emergent-incidents]&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;DARPA&amp;#039;s Low Resource Languages for Emergent Incidents  (LORELEI)] program [https://www.darpa.mil/program/low-resource-languages-for-emergent-incidents]&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;−&quot;&gt;&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;is focused  on enabling  low-cost development of capabilities for low-resource languages, targeted at humanitarian assistance and disaster relief [https://health.mil/Military-Health-Topics/Health-Readiness/Global-Health-Engagement/Humanitarian-Assistance-and-Disaster-Relief HADR] in the aftermath of a crisis like an earthquake, tsunami, or epidemic.  In this project we are developing new technologies for quickly ramping up the ability to extract actionable information from online sources related to both population needs (e.g. food or water shortages, lack of shelter, need for medical assistance) and population mental state (e.g. fear, anger).  Methodologically we are focused on advanced topic models and combinations of topic models with deep learning methods.&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;+&quot;&gt;&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;is focused  on enabling  low-cost development of capabilities for low-resource languages, targeted at humanitarian assistance and disaster relief &lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;(&lt;/ins&gt;[https://health.mil/Military-Health-Topics/Health-Readiness/Global-Health-Engagement/Humanitarian-Assistance-and-Disaster-Relief HADR]&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;) &lt;/ins&gt;in the aftermath of a crisis like an earthquake, tsunami, or epidemic.  In this project we are developing new technologies for quickly ramping up the ability to extract actionable information from online sources related to both population needs (e.g. food or water shortages, lack of shelter, need for medical assistance) and population mental state (e.g. fear, anger).  Methodologically we are focused on advanced topic models and combinations of topic models with deep learning methods.&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>Louiqa</name></author>
	</entry>
	<entry>
		<id>https://wiki.umiacs.umd.edu/clip/index.php?title=HumAssist&amp;diff=939&amp;oldid=prev</id>
		<title>Louiqa at 05:19, 8 December 2017</title>
		<link rel="alternate" type="text/html" href="https://wiki.umiacs.umd.edu/clip/index.php?title=HumAssist&amp;diff=939&amp;oldid=prev"/>
		<updated>2017-12-08T05:19:51Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;table style=&quot;background-color: #fff; color: #202122;&quot; data-mw=&quot;interface&quot;&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
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				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;Revision as of 05:19, 8 December 2017&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l1&quot;&gt;Line 1:&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;Line 1:&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;DARPA&amp;#039;s Low Resource Languages for Emergent Incidents  (LORELEI)] program [https://www.darpa.mil/program/low-resource-languages-for-emergent-incidents]&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;DARPA&amp;#039;s Low Resource Languages for Emergent Incidents  (LORELEI)] program [https://www.darpa.mil/program/low-resource-languages-for-emergent-incidents]&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;−&quot;&gt;&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;is focused  on enabling  low-cost development of capabilities for low-resource languages, targeted at humanitarian assistance and disaster relief&lt;del style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;, HADR &lt;/del&gt;[https://health.mil/Military-Health-Topics/Health-Readiness/Global-Health-Engagement/Humanitarian-Assistance-and-Disaster-Relief HADR] in the aftermath of a crisis like an earthquake, tsunami, or epidemic.  In this project we are developing new technologies for quickly ramping up the ability to extract actionable information from online sources related to both population needs (e.g. food or water shortages, lack of shelter, need for medical assistance) and population mental state (e.g. fear, anger).  Methodologically we are focused on advanced topic models and combinations of topic models with deep learning methods.&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;+&quot;&gt;&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;is focused  on enabling  low-cost development of capabilities for low-resource languages, targeted at humanitarian assistance and disaster relief [https://health.mil/Military-Health-Topics/Health-Readiness/Global-Health-Engagement/Humanitarian-Assistance-and-Disaster-Relief HADR] in the aftermath of a crisis like an earthquake, tsunami, or epidemic.  In this project we are developing new technologies for quickly ramping up the ability to extract actionable information from online sources related to both population needs (e.g. food or water shortages, lack of shelter, need for medical assistance) and population mental state (e.g. fear, anger).  Methodologically we are focused on advanced topic models and combinations of topic models with deep learning methods.&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>Louiqa</name></author>
	</entry>
	<entry>
		<id>https://wiki.umiacs.umd.edu/clip/index.php?title=HumAssist&amp;diff=938&amp;oldid=prev</id>
		<title>Louiqa: Created page with &quot;DARPA&#039;s Low Resource Languages for Emergent Incidents  (LORELEI)] program [https://www.darpa.mil/program/low-resource-languages-for-emergent-incidents] is focused  on enablin...&quot;</title>
		<link rel="alternate" type="text/html" href="https://wiki.umiacs.umd.edu/clip/index.php?title=HumAssist&amp;diff=938&amp;oldid=prev"/>
		<updated>2017-12-08T05:19:26Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;DARPA&amp;#039;s Low Resource Languages for Emergent Incidents  (LORELEI)] program [https://www.darpa.mil/program/low-resource-languages-for-emergent-incidents] is focused  on enablin...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;DARPA&amp;#039;s Low Resource Languages for Emergent Incidents  (LORELEI)] program [https://www.darpa.mil/program/low-resource-languages-for-emergent-incidents]&lt;br /&gt;
is focused  on enabling  low-cost development of capabilities for low-resource languages, targeted at humanitarian assistance and disaster relief, HADR [https://health.mil/Military-Health-Topics/Health-Readiness/Global-Health-Engagement/Humanitarian-Assistance-and-Disaster-Relief HADR] in the aftermath of a crisis like an earthquake, tsunami, or epidemic.  In this project we are developing new technologies for quickly ramping up the ability to extract actionable information from online sources related to both population needs (e.g. food or water shortages, lack of shelter, need for medical assistance) and population mental state (e.g. fear, anger).  Methodologically we are focused on advanced topic models and combinations of topic models with deep learning methods.&lt;/div&gt;</summary>
		<author><name>Louiqa</name></author>
	</entry>
</feed>