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 <channel rdf:about="http://ebiquity.umbc.edu/tag/datamining/">
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    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/333/On-Mining-Web-Access-Logs"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/238/Probabilistic-Approximate-Algorithms-for-Distributed-Data-Mining-in-Peer-to-Peer-Networks"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/237/Research-Challenges-In-Data-Mining"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/215/Empowering-Scientific-Discovery-by-Distributed-Data-Mining-on-the-Grid-Infrastructure"/>
    <rdf:li resource="http://ebiquity.umbc.edu/blogger/2008/04/21/Jiawei-Han:-Research-Challenges-In-Data-Mining,-10am-4/22-LH8-UMBC/"/>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/333/On-Mining-Web-Access-Logs">
  <title><![CDATA[On Mining Web Access Logs]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/333/On-Mining-Web-Access-Logs</link>
  <description><![CDATA[The proliferation of information on the world wide web has made
the personalization of this information space a necessity. One
possible approach to web personalization is to mine typical user
profiles from the vast amount of historical data stored in access
logs. In the absence of any a priori knowledge, unsupervised
classification or clustering methods seem to be ideally suited to
analyze the semi-structured log data of user accesses. In this paper,
we define the notion of a “user s...]]></description>
  <dc:date>2000-05-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/238/Probabilistic-Approximate-Algorithms-for-Distributed-Data-Mining-in-Peer-to-Peer-Networks">
  <title><![CDATA[Probabilistic Approximate Algorithms for Distributed Data Mining in Peer-to-Peer Networks]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/238/Probabilistic-Approximate-Algorithms-for-Distributed-Data-Mining-in-Peer-to-Peer-Networks</link>
  <description><![CDATA[Peer-to-peer(P2P) computing is emerging as a new distributed computing 
paradigm for novel applications that involves exchange of information 
among  peers with little centralized coordination. Analyzing data 
distributed in P2P networks requires peer-to-peer data mining algorithms 
that can mine the data without data centralization. However, 
replicating  result of centralized data mining in an exact fashion is 
often communication-wise expensive. Approximate algorithms can be a 
real...]]></description>
  <dc:date>2008-04-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/237/Research-Challenges-In-Data-Mining">
  <title><![CDATA[Research Challenges In Data Mining]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/237/Research-Challenges-In-Data-Mining</link>
  <description><![CDATA[Research in data mining has led to advanced knowledge discovery
technologies and applications. In this talk, we will discuss some
emerging research issues for advanced technologies and
applications in data mining and discuss some recent progress in
this direction, including (1) exploration of the power of pattern
mining, (2) analysis of multidimensional, heterogeneous and
evolving information network, (3) mining of fast changing data
streams, (4) mining of moving object data, RFID data...]]></description>
  <dc:date>2008-04-22</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/215/Empowering-Scientific-Discovery-by-Distributed-Data-Mining-on-the-Grid-Infrastructure">
  <title><![CDATA[Empowering Scientific Discovery by Distributed Data Mining on the Grid Infrastructure]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/215/Empowering-Scientific-Discovery-by-Distributed-Data-Mining-on-the-Grid-Infrastructure</link>
  <description><![CDATA[The grid-based computing paradigm has attracted much attention in recent years. The sharing of distributed computing resources (such as software, hardware, data, sensors, etc) is an important aspect of grid computing. Computational Grids focus on methods for handling compute intensive tasks while Data Grids are geared toward data-intensive computing. Grid-based computing has been put to use in several scientific disciplines such as astronomy, engineering, climate studies, ecology, biology and...]]></description>
  <dc:date>2007-09-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/blogger/2008/04/21/Jiawei-Han:-Research-Challenges-In-Data-Mining,-10am-4/22-LH8-UMBC/">
  <title><![CDATA[Jiawei Han: Research Challenges In Data Mining, 10am 4/22 LH8 UMBC]]></title>
  <link>http://ebiquity.umbc.edu/blogger/2008/04/21/Jiawei-Han:-Research-Challenges-In-Data-Mining,-10am-4/22-LH8-UMBC/</link>
  <description><![CDATA[Jiawei Han will give a talk tomorrow, Research Challenges In Data Mining at 10am in UMBC's
LH8 (1st floor ITE building).  Here's the abstract.  
"Research in data mining has led to advanced knowledge discovery technologies and applications. In this talk, we will discuss some emerging research issues for advanced technologies and applications in data mining and discuss some recent progress in this direction, including (1) exploration of the power of pattern mining, (2) analysis of multidimen...]]></description>
  <dc:date>2008-04-21</dc:date>
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