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	<title>Comments for Cool/Snap?</title>
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	<link>http://www.coolsnap.net/kevin</link>
	<description>Almost, but not quite, entirely unlike discourse</description>
	<lastBuildDate>Mon, 18 Feb 2008 08:12:49 +0000</lastBuildDate>
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		<title>Comment on Bloom Filters by hobbes_dmS</title>
		<link>http://www.coolsnap.net/kevin/?p=13&#038;cpage=1#comment-105</link>
		<dc:creator>hobbes_dmS</dc:creator>
		<pubDate>Mon, 18 Feb 2008 08:12:49 +0000</pubDate>
		<guid isPermaLink="false">http://www.coolsnap.net/kevin/?p=13#comment-105</guid>
		<description>I noticed that you calculate the hashindices on each for-loop in your function _HashIndices(). If you except larger quantities of words (like &gt;500.000) to be inserted into a big Bloomfilter (600kB Bitvec) you&#039;ll get an optimum number of 7 Hashfunctions... calculating 2 Hashvalues might then be a little faster than calculating 14 Hashvalues for each word ;)

greetings</description>
		<content:encoded><![CDATA[<p>I noticed that you calculate the hashindices on each for-loop in your function _HashIndices(). If you except larger quantities of words (like &gt;500.000) to be inserted into a big Bloomfilter (600kB Bitvec) you&#8217;ll get an optimum number of 7 Hashfunctions&#8230; calculating 2 Hashvalues might then be a little faster than calculating 14 Hashvalues for each word <img src='http://www.coolsnap.net/kevin/wp-includes/images/smilies/icon_wink.gif' alt=';)' class='wp-smiley' /> </p>
<p>greetings</p>
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		<title>Comment on FYI by md</title>
		<link>http://www.coolsnap.net/kevin/?p=43&#038;cpage=1#comment-7</link>
		<dc:creator>md</dc:creator>
		<pubDate>Sat, 21 Jul 2007 17:02:31 +0000</pubDate>
		<guid isPermaLink="false">http://www.coolsnap.net/kevin/?p=43#comment-7</guid>
		<description>Congrats on the new gig. AdMob is doing great things and the team is first rate. I am a friend of the company and am happy to say that there are many former students and colleagues working there. Omar is a terrific CEO and continues to build a great team. Break a leg!</description>
		<content:encoded><![CDATA[<p>Congrats on the new gig. AdMob is doing great things and the team is first rate. I am a friend of the company and am happy to say that there are many former students and colleagues working there. Omar is a terrific CEO and continues to build a great team. Break a leg!</p>
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		<title>Comment on Linguistic Anthropology by cheesewz</title>
		<link>http://www.coolsnap.net/kevin/?p=26&#038;cpage=1#comment-5</link>
		<dc:creator>cheesewz</dc:creator>
		<pubDate>Wed, 13 Jun 2007 18:27:10 +0000</pubDate>
		<guid isPermaLink="false">http://www.coolsnap.net/kevin/?p=26#comment-5</guid>
		<description>This article was right on the money. Pretty much summed up my entire online community.</description>
		<content:encoded><![CDATA[<p>This article was right on the money. Pretty much summed up my entire online community.</p>
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		<title>Comment on Bloom Filters by Cool/Snap? &#187; More Fun With Bloom Filters</title>
		<link>http://www.coolsnap.net/kevin/?p=13&#038;cpage=1#comment-3</link>
		<dc:creator>Cool/Snap? &#187; More Fun With Bloom Filters</dc:creator>
		<pubDate>Sat, 28 Apr 2007 22:44:37 +0000</pubDate>
		<guid isPermaLink="false">http://www.coolsnap.net/kevin/?p=13#comment-3</guid>
		<description>[...] In my previous Bloom filter post, I talked about using Bloom filters for spell checking in memory constrained environments. With respect to problems like spell checking, contemporary machines can&#8217;t exactly be described as memory constrained. One can easily load a comprehensive language dictionary into a few megs of memory and store it in an ordinary hash table, trie, or other structure for efficient lookups. [...]</description>
		<content:encoded><![CDATA[<p>[...] In my previous Bloom filter post, I talked about using Bloom filters for spell checking in memory constrained environments. With respect to problems like spell checking, contemporary machines can&#8217;t exactly be described as memory constrained. One can easily load a comprehensive language dictionary into a few megs of memory and store it in an ordinary hash table, trie, or other structure for efficient lookups. [...]</p>
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