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	<title>Joseph Wilk &#187; Python</title>
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	<link>http://blog.josephwilk.net</link>
	<description>on AI, The Web, Usability, Testing &#38; Software process</description>
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		<title>Automatic Admin Systems &#8211; Semantics with Rails &amp; Django</title>
		<link>http://blog.josephwilk.net/critique/automatic-admin-systems-semantics-with-rails-and-django.html</link>
		<comments>http://blog.josephwilk.net/critique/automatic-admin-systems-semantics-with-rails-and-django.html#comments</comments>
		<pubDate>Fri, 18 Jan 2008 11:52:59 +0000</pubDate>
		<dc:creator>Joseph Wilk</dc:creator>
				<category><![CDATA[Critique]]></category>
		<category><![CDATA[Django]]></category>
		<category><![CDATA[Python]]></category>
		<category><![CDATA[Rails]]></category>
		<category><![CDATA[Ruby]]></category>
		<category><![CDATA[Semantics]]></category>

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		<description><![CDATA[The Magically Appearing Admin Web developers using an MVC framework produce their websites playing with their models, views and controllers. Then by adding a few lines of magic an admin system appears which allows users to add/edit/delete/view/search their models. Examples: Django&#8217;s Magic Admin (Also NewFormsAdmin &#8211; a branch of Django focused on making it easier [...]]]></description>
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		<slash:comments>0</slash:comments>
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		<title>Latent Semantic Analysis in Python</title>
		<link>http://blog.josephwilk.net/projects/latent-semantic-analysis-in-python.html</link>
		<comments>http://blog.josephwilk.net/projects/latent-semantic-analysis-in-python.html#comments</comments>
		<pubDate>Wed, 19 Dec 2007 11:14:42 +0000</pubDate>
		<dc:creator>Joseph Wilk</dc:creator>
				<category><![CDATA[Information retrieval]]></category>
		<category><![CDATA[Projects]]></category>
		<category><![CDATA[Datamining]]></category>
		<category><![CDATA[Python]]></category>
		<category><![CDATA[Search]]></category>

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		<description><![CDATA[Latent Semantic Analysis (LSA) is a mathematical method that tries to bring out latent relationships within a collection of documents. Rather than looking at each document isolated from the others it looks at all the documents as a whole and the terms within them to identify relationships. An example of LSA: Using a search engine [...]]]></description>
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		<slash:comments>11</slash:comments>
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		<item>
		<title>Building a Vector Space Search Engine in Python</title>
		<link>http://blog.josephwilk.net/projects/building-a-vector-space-search-engine-in-python.html</link>
		<comments>http://blog.josephwilk.net/projects/building-a-vector-space-search-engine-in-python.html#comments</comments>
		<pubDate>Tue, 27 Nov 2007 08:08:49 +0000</pubDate>
		<dc:creator>Joseph Wilk</dc:creator>
				<category><![CDATA[Critique]]></category>
		<category><![CDATA[Information retrieval]]></category>
		<category><![CDATA[Projects]]></category>
		<category><![CDATA[Datamining]]></category>
		<category><![CDATA[Python]]></category>
		<category><![CDATA[Search]]></category>
		<category><![CDATA[Vectors]]></category>

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		<description><![CDATA[A vector space search involves converting documents into vectors. Each dimension within the vectors represents a term. If a document contains that term then the value within the vector is greater than zero. Here is an implementation of Vector space searching using python (2.4+). 1 Stemming &#38; Stop words Fetch all terms within documents and [...]]]></description>
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		<slash:comments>9</slash:comments>
		</item>
		<item>
		<title>Funkload Build script</title>
		<link>http://blog.josephwilk.net/utilities/funkload-build-script.html</link>
		<comments>http://blog.josephwilk.net/utilities/funkload-build-script.html#comments</comments>
		<pubDate>Fri, 23 Nov 2007 10:10:32 +0000</pubDate>
		<dc:creator>Joseph Wilk</dc:creator>
				<category><![CDATA[Utilities]]></category>
		<category><![CDATA[Python]]></category>
		<category><![CDATA[Testing]]></category>

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		<description><![CDATA[Funkload is an open source python based unit testing tool. It serves as a good tool for load testing. We can use it to create a unit test which simulates a user browsing through a site. To test load run two simultaneous instances of the unit test and so on scaling up the number of [...]]]></description>
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		<slash:comments>0</slash:comments>
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		<item>
		<title>Keeping the Cache Hot</title>
		<link>http://blog.josephwilk.net/projects/keeping-the-cache-hot.html</link>
		<comments>http://blog.josephwilk.net/projects/keeping-the-cache-hot.html#comments</comments>
		<pubDate>Thu, 15 Nov 2007 14:03:48 +0000</pubDate>
		<dc:creator>Joseph Wilk</dc:creator>
				<category><![CDATA[Projects]]></category>
		<category><![CDATA[cache]]></category>
		<category><![CDATA[Python]]></category>

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		<description><![CDATA[Problem The exipry of content within caching architectures is only identified when a user makes a request for expired data. Hence a % of the visitors to the site will not be able to take advantage of caching.Many different caching architectures are used within a typical dynamic site. Hence the solution needs to be cache [...]]]></description>
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		<slash:comments>0</slash:comments>
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