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	Comments on: Expertise location: linking social networks and text mining	</title>
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	<description>Keynote speaker &#124; Futurist &#124; Strategy advisor</description>
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		By: Anish K.S		</title>
		<link>https://rossdawson.com/expertise_locat/#comment-449</link>

		<dc:creator><![CDATA[Anish K.S]]></dc:creator>
		<pubDate>Fri, 07 Nov 2008 01:48:20 +0000</pubDate>
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					<description><![CDATA[i am very much interested in Social bookmarking.
]]></description>
			<content:encoded><![CDATA[<p>i am very much interested in Social bookmarking.</p>
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		<title>
		By: Samuel		</title>
		<link>https://rossdawson.com/expertise_locat/#comment-448</link>

		<dc:creator><![CDATA[Samuel]]></dc:creator>
		<pubDate>Thu, 30 Oct 2008 05:26:15 +0000</pubDate>
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					<description><![CDATA[Great post. I agree that using &#039;intelligent text mining&#039; is an interesting approach to expertise location in companies (and on the internet). We experimented with this some time ago in our company with interesting results. This experiment was set up because - as we all experience - employees fill in their Yellow Page profile, but don&#039;t keep them up to date. Relating the filled-in profile to mining could trigger employees to keep it up to date. And it could also (partially) fill in their profile.
We also combined this with a more social approach, which is now being capitalized in Guruscan(.nl). Because using mining to find and define expertise limits you to what&#039;s in databases. And when we write reports about a tool, we don&#039;t mention we&#039;re very good at PERL programming for instance. So, this social layer collects the tacit stuff.
Here are some references:
- Samuel Driessen, Willem-Olaf Huijsen, Marjan Grootveld, “A framework for evaluating knowledge-mapping tools”, Journal of Knowledge Management, 2007, Vol. 11, Iss. 2, page 109-117.
- Willem-Olaf Huijsen, Samuël J. Driessen, Dion Slijp, &quot;ExpertFinder: Collaborative Expertise Localization&quot;, I-Media 2007.
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			<content:encoded><![CDATA[<p>Great post. I agree that using &#8216;intelligent text mining&#8217; is an interesting approach to expertise location in companies (and on the internet). We experimented with this some time ago in our company with interesting results. This experiment was set up because &#8211; as we all experience &#8211; employees fill in their Yellow Page profile, but don&#8217;t keep them up to date. Relating the filled-in profile to mining could trigger employees to keep it up to date. And it could also (partially) fill in their profile.<br />
We also combined this with a more social approach, which is now being capitalized in Guruscan(.nl). Because using mining to find and define expertise limits you to what&#8217;s in databases. And when we write reports about a tool, we don&#8217;t mention we&#8217;re very good at PERL programming for instance. So, this social layer collects the tacit stuff.<br />
Here are some references:<br />
&#8211; Samuel Driessen, Willem-Olaf Huijsen, Marjan Grootveld, “A framework for evaluating knowledge-mapping tools”, Journal of Knowledge Management, 2007, Vol. 11, Iss. 2, page 109-117.<br />
&#8211; Willem-Olaf Huijsen, Samuël J. Driessen, Dion Slijp, &#8220;ExpertFinder: Collaborative Expertise Localization&#8221;, I-Media 2007.</p>
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