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	<title>Comments on: OpenCalais on Jobs Data</title>
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	<link>http://blog.likematter.com/2008/04/16/opencalais-on-jobs-data/</link>
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	<pubDate>Thu, 29 Jul 2010 12:31:56 +0000</pubDate>
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		<title>By: Michael Shilman</title>
		<link>http://blog.likematter.com/2008/04/16/opencalais-on-jobs-data/comment-page-1/#comment-12</link>
		<dc:creator>Michael Shilman</dc:creator>
		<pubDate>Thu, 17 Apr 2008 16:27:08 +0000</pubDate>
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		<description>Nice!  I'm curious how Yahoo's entity extractor stacks up: http://pipes.yahoo.com/pipes/pipes.popular</description>
		<content:encoded><![CDATA[<p>Nice!  I&#8217;m curious how Yahoo&#8217;s entity extractor stacks up: <a href="http://pipes.yahoo.com/pipes/pipes.popular" rel="nofollow">http://pipes.yahoo.com/pipes/pipes.popular</a></p>
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		<title>By: Tom Tague</title>
		<link>http://blog.likematter.com/2008/04/16/opencalais-on-jobs-data/comment-page-1/#comment-11</link>
		<dc:creator>Tom Tague</dc:creator>
		<pubDate>Wed, 16 Apr 2008 21:29:06 +0000</pubDate>
		<guid isPermaLink="false">http://blog.alluviallabs.com/2008/04/16/opencalais-on-jobs-data/#comment-11</guid>
		<description>Mark:

Tom Tague from Calais here.

What a great experiment. I'm constantly amazed at the new ways being are attempting to get value out of Calais - things we never would have thought of ourselves. 

What you're addressing here is fundamentally interesting and a good proof point for some of the issues we're all having with search as primary tool for information discovery. As you point out: search works fine if you know what to search for. It's a pretty poor discovery tool.

In the upcoming release of Calais we're rolling out our first experiments in using open data sources (such as Wikipedia and others) to improve recognition of certain types of entities. This first experiment is going to be a small foray into the area of popular culture (entertainment and sports), but it is also serving to help us learn how to leverage these data assets.

In the near future we'll be able to increase our intelligence by dozens of entity types per month - and I'm certain this will include items such as technologies. We're also investigating some "near real time" options where entities could be discovered in the morning - and we'd be able to categorize and type them within a few hours.

Thanks again for taking the time to do such a thoughtful experiment.</description>
		<content:encoded><![CDATA[<p>Mark:</p>
<p>Tom Tague from Calais here.</p>
<p>What a great experiment. I&#8217;m constantly amazed at the new ways being are attempting to get value out of Calais - things we never would have thought of ourselves. </p>
<p>What you&#8217;re addressing here is fundamentally interesting and a good proof point for some of the issues we&#8217;re all having with search as primary tool for information discovery. As you point out: search works fine if you know what to search for. It&#8217;s a pretty poor discovery tool.</p>
<p>In the upcoming release of Calais we&#8217;re rolling out our first experiments in using open data sources (such as Wikipedia and others) to improve recognition of certain types of entities. This first experiment is going to be a small foray into the area of popular culture (entertainment and sports), but it is also serving to help us learn how to leverage these data assets.</p>
<p>In the near future we&#8217;ll be able to increase our intelligence by dozens of entity types per month - and I&#8217;m certain this will include items such as technologies. We&#8217;re also investigating some &#8220;near real time&#8221; options where entities could be discovered in the morning - and we&#8217;d be able to categorize and type them within a few hours.</p>
<p>Thanks again for taking the time to do such a thoughtful experiment.</p>
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