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    <description>Recent content on Digital.gov</description>
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      <title>From Elephant to ELK: How We Migrated Our Analytics System to Elasticsearch</title>
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      <pubDate>Wed, 07 Jan 2015 11:15:44 -0400</pubDate>
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      <description>As I mentioned in a recent blog post about image search, we’re avid users of Elasticsearch for search. We also recently ported another vital part of our system to Elasticsearch: analytics. This post is a technical deep dive into how our analytics system works, and specifically how and why we used Elasticsearch to build it. Background DigitalGov Search is</description>
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      <title>A Picture Is Worth a Thousand Tokens: Part II</title>
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      <pubDate>Tue, 04 Nov 2014 10:00:48 -0400</pubDate>
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      <description>In the first part of A Picture Is Worth a Thousand Tokens, I explained why we built a social media-driven image search engine, and specifically how we used Elasticsearch to build its first iteration. In this week’s post, I’ll take a deep dive into how we worked to improve relevancy, recall, and the searcher’s experience</description>
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      <title>A Picture Is Worth a Thousand Tokens</title>
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      <pubDate>Tue, 28 Oct 2014 11:15:34 -0400</pubDate>
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      <description>Increasingly, we’ve noticed that our agency customers are publishing their highest quality images on social media and within database-driven multimedia galleries on their websites. These sources are curated, contain metadata, and have both thumbnails and full-size images. That’s a big improvement in quality over the images embedded within HTML pages on agencies’ websites. After some</description>
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