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	<title>Comments on: Review of &#8220;The Link Prediction Problem for Social Networks&#8221;</title>
	<atom:link href="http://kallander.net/will/blog/2008/05/22/review-of-the-link-prediction-problem-for-social-networks/feed/" rel="self" type="application/rss+xml" />
	<link>http://kallander.net/will/blog/2008/05/22/review-of-the-link-prediction-problem-for-social-networks/</link>
	<description>Random rumblings, rants, and reflections</description>
	<pubDate>Tue, 06 Jan 2009 21:29:58 +0000</pubDate>
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		<title>By: wkallander</title>
		<link>http://kallander.net/will/blog/2008/05/22/review-of-the-link-prediction-problem-for-social-networks/comment-page-1/#comment-89</link>
		<dc:creator>wkallander</dc:creator>
		<pubDate>Tue, 10 Jun 2008 09:16:44 +0000</pubDate>
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		<description>I just discovered this paper: 
Hasan, M., Chaoji, V., Salem, S., and Zaki, M. J., (2006). "Link Prediction using Supervised Learning," Workshop on Link Analysis, Counter-terrorism and Security (with SIAM Data Mining Conference), Bethesda, MD, April 2006.

...which discusses an attempt to use attribute data as I suggested in my review (they beat me to it!).  It does occur to me however, that doing so sacrifices generality.  Part of the beauty of Liben-Nowell and Kleinberg's approach is that it can be applied to any social network, without having to do feature selection.</description>
		<content:encoded><![CDATA[<p>I just discovered this paper:<br />
Hasan, M., Chaoji, V., Salem, S., and Zaki, M. J., (2006). &#8220;Link Prediction using Supervised Learning,&#8221; Workshop on Link Analysis, Counter-terrorism and Security (with SIAM Data Mining Conference), Bethesda, MD, April 2006.</p>
<p>&#8230;which discusses an attempt to use attribute data as I suggested in my review (they beat me to it!).  It does occur to me however, that doing so sacrifices generality.  Part of the beauty of Liben-Nowell and Kleinberg&#8217;s approach is that it can be applied to any social network, without having to do feature selection.</p>
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