<?xml version="1.0" encoding="UTF-8"?>
<!-- generator="FeedCreator 1.8" -->
<?xml-stylesheet href="http://servo.ad.wlu.edu/dokuwiki/lib/exe/css.php?s=feed" type="text/css"?>
<rdf:RDF
    xmlns="http://purl.org/rss/1.0/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
    xmlns:dc="http://purl.org/dc/elements/1.1/">
    <channel rdf:about="http://servo.ad.wlu.edu/dokuwiki/feed.php">
        <title>W&amp;L Computer Science Wiki - courses:cs211:winter2014:journals:eric</title>
        <description></description>
        <link>http://servo.ad.wlu.edu/dokuwiki/</link>
        <image rdf:resource="http://servo.ad.wlu.edu/dokuwiki/lib/exe/fetch.php/wiki/dokuwiki-128.png" />
       <dc:date>2026-04-23T04:55:26+00:00</dc:date>
        <items>
            <rdf:Seq>
                <rdf:li rdf:resource="http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2014/journals/eric/home?rev=1396276568&amp;do=diff"/>
            </rdf:Seq>
        </items>
    </channel>
    <image rdf:about="http://servo.ad.wlu.edu/dokuwiki/lib/exe/fetch.php/wiki/dokuwiki-128.png">
        <title>W&L Computer Science Wiki</title>
        <link>http://servo.ad.wlu.edu/dokuwiki/</link>
        <url>http://servo.ad.wlu.edu/dokuwiki/lib/exe/fetch.php/wiki/dokuwiki-128.png</url>
    </image>
    <item rdf:about="http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2014/journals/eric/home?rev=1396276568&amp;do=diff">
        <dc:format>text/html</dc:format>
        <dc:date>2014-03-31T14:36:08+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>home</title>
        <link>http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2014/journals/eric/home?rev=1396276568&amp;do=diff</link>
        <description>Eric&#039;s Journal

Interest: 7/10. this is back to bit too abstract for me. maybe (in fact probably) this week&#039;s reading will help out if I take big data class this fall. it seems network flow would be huge part of big data since it&#039;s about partitioning too big a set to compute with x resources into smaller sets with x*y resources</description>
    </item>
</rdf:RDF>
