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 <channel rdf:about="http://ebiquity.umbc.edu/tag/user modeling/">
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  <image rdf:resource="http://ebiquity.umbc.edu/img/logo.jpg" />  <title><![CDATA[RSS Tag Search]]></title>
  <link>http://ebiquity.umbc.edu/tag/user modeling/</link>
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    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/38/Profile-Driven-Data-Management-for-Pervasive-Environments"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/287/Modeling-the-user-in-natural-language-systems"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/325/GUMS-A-General-User-Modeling-System"/>
    <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/199/Personalized-Information-Retrieval-in-Context"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/236/Improved-Information-Retrieval-through-Set-Based-Preference"/>
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 <image rdf:about="http://ebiquity.umbc.edu/img/logo.jpg">
  <title>UMBC ebiquity research group</title>
  <link>http://ebiquity.umbc.edu</link>
  <url>http://ebiquity.umbc.edu/img/logo.jpg</url>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/38/Profile-Driven-Data-Management-for-Pervasive-Environments">
  <title><![CDATA[Profile Driven Data Management for Pervasive Environments]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/38/Profile-Driven-Data-Management-for-Pervasive-Environments</link>
  <description><![CDATA[The past few years have seen significant work in mobile data management,
typically based on the client/proxy/server model. Mobile/wireless devices
are treated as clients that are data consumers only, while data sources are on
servers that typically reside on the wired network. With the advent of "pervasive
computing" environments an alternative scenario arises where mobile devices
gather and exchange data from not just wired sources, but also from their ethereal
environment and one anot...]]></description>
  <dc:date>2002-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/287/Modeling-the-user-in-natural-language-systems">
  <title><![CDATA[Modeling the user in natural language systems]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/287/Modeling-the-user-in-natural-language-systems</link>
  <description><![CDATA[For intelligent interactive systems to communicate with humans in a natural manner, they must have knowledge about the system users. This paper explores the role of user modeling in such systems. It begins with a characterization of what a user model is and how it can be used. The types of information that a user model may be required to keep about a user are then identified and discussed. User models themselves can vary greatly depending on the requirements of the situation and the implement...]]></description>
  <dc:date>1988-01-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/325/GUMS-A-General-User-Modeling-System">
  <title><![CDATA[GUMS: A General User Modeling System]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/325/GUMS-A-General-User-Modeling-System</link>
  <description><![CDATA[This paper describes a general architecture of a domain independent
system for building and maintaining ling term models of individual
users..The user modeling system is intended Io provide a well
defined set of services for an application system which is interacting
with various users and has a need to build and maintain models of
them. As the application system interacts with a user, it can acquire
knowledge of him and pass that knowledge on 1o the user model
maintenance system for i...]]></description>
  <dc:date>1986-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/199/Personalized-Information-Retrieval-in-Context">
  <title><![CDATA[Personalized Information Retrieval in Context]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/199/Personalized-Information-Retrieval-in-Context</link>
  <description><![CDATA[Personalized content retrieval aims at improving the retrieval process by taking into account the particular interests of individual users. However, not all user preferences are relevant in all situations. It is well known that human preferences are complex, multiple, heterogeneous, changing, even contradictory, and should be understood in context with the user goals and tasks at hand. We propose a method to build a dynamic representation of the semantic context of ongoing retrieval tasks, wh...]]></description>
  <dc:date>2006-09-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/236/Improved-Information-Retrieval-through-Set-Based-Preference">
  <title><![CDATA[Improved Information Retrieval through Set-Based Preference]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/236/Improved-Information-Retrieval-through-Set-Based-Preference</link>
  <description><![CDATA[I present a new information retrieval framework based on set-based
preference learning that provides users with individually customized
search results. Advances in information storage and retrieval have
enabled computer users to search immense data repositories for very
specific content. While newer information retrieval algorithms can
provide a much richer result set than traditional term-weighting
methods, they adopt a one-size-fits-all approach. By analyzing a
user's prior sea...]]></description>
  <dc:date>2008-04-25</dc:date>
 </item>
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